SAP BUSSINESS INTELLIGENCE

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SAP BW Patni Computer Systems Ltd. SAP BW Student Guide Version 1.0 01 st July 2007 Copyright © 2006 Patni Computer Systems Ltd., Akruti, MIDC Cross Road No. 21, Andheri (E), Mumbai 400 093. All rights reserved. No part of this publication can be Patni Internal Page 1 of 251

description

Covers the whole BI

Transcript of SAP BUSSINESS INTELLIGENCE

Page 1: SAP BUSSINESS INTELLIGENCE

SAP BW

Patni Computer Systems Ltd.

SAP BWStudent

GuideVersion 1.001st July 2007

Copyright © 2006 Patni Computer Systems Ltd., Akruti, MIDC Cross Road No. 21, Andheri (E), Mumbai 400 093. All rights reserved. No part of this publication can be reproduced in any way, including but not limited to photocopy, photographic, magnetic, or other record, without the prior agreement and written permission of Patni Computer Systems.

Patni Computer Systems considers information included in this document to be Confidential and Proprietary.

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Table of contents

1 INTRODUCTION TO BUSINESS INTELLIGENCE & DATA WAREHOUSING..........................................................................................................4

1.1. BUSINESS INTELLIGENCE AND DATA WAREHOUSING....................................41.2. THE CLASSIC STAR SCHEMA..........................................................................51.3. INTRODUCTION TO SAP BW..........................................................................61.4. SAP BW ARCHITECTURE...............................................................................71.5. THE SAP BW STAR SCHEMA........................................................................91.6. INTRODUCTION TO ADMINISTRATOR WORKBENCH (AWB)........................14

2 INTRODUCTION TO INFOOBJECTS & INFOCUBES.............................17

2.1. INTRODUCTION TO INFOOBJECTS.................................................................172.2. TYPES OF INFOOBJECTS...............................................................................172.3. CHARACTERISTIC INFOOBJECT....................................................................192.4. CREATING A CHARACTERISTIC IN THE INFOOBJECT TREE..........................292.5. KEY FIGURES...............................................................................................312.6. INFOCUBES...................................................................................................352.7. BASISCUBES.................................................................................................362.8. CREATING AN INFOCUBE IN THE INFOPROVIDER TREE...............................402.9. TECHNICAL IMPLEMENTATION OF SAP BW STAR SCHEMA........................43

3 DATA TRANSFER PROCESS IN SAP BI.....................................................59

3.1. OVERVIEW OF DATA TRANSFER PROCESS...................................................593.2. DATA TRANSFER PROCESS – EXAMPLE.......................................................613.3. CREATING AND MANAGING DTP.................................................................623.4. ERROR HANDLING OF DTP..........................................................................673.5. ERROR STACK IN DTP.................................................................................683.6. TEMPORARY STORAGE FOR DTP.................................................................723.7. DTP MONITOR.............................................................................................743.8. MANAGING INFOCUBES-DATA MAINTENANCE...........................................803.9. USING BW MONITOR...................................................................................93

4 DATA STORE OBJECTS (DSO)....................................................................98

4.1. DATA STORE OBJECT DEFINITION:...............................................................984.2. DATA STORE OBJECT TYPES......................................................................1004.3. DATA STORE OBJECT ADMINISTRATION....................................................1074.4. DATASTORE OBJECT ADMINISTRATION - PERFORMANCE:........................110

5 MULTIPROVIDERS......................................................................................112

5.1. ADVANTAGES OF MULTIPROVIDER............................................................1135.2. MULTIPROVIDER, APPLICATION EXAMPLE................................................1135.3. CREATING A MULTIPROVIDER...................................................................116

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6 AGGREGATES...............................................................................................119

6.1. USING AGGREGATES..................................................................................1196.2. AGGREGATES AND MASTER DATA CHANGES............................................125

7 ADMIN COCKPIT..........................................................................................132

8 PROCESS CHAINS........................................................................................132

8.1. OVERVIEW OF PROCESS CHAINS................................................................1328.2. STRUCTURE OF PROCESS CHAINS..............................................................133

9 GENERIC R/3 DATA EXTRACTION.........................................................137

9.1. CREATING VIEWS IN R/3............................................................................1379.2. CREATING DATASOURCES IN R/3..............................................................1399.3. LOADING DATA FROM R/3 INTO BW.........................................................140

10 LOGISTICS COCKPIT..............................................................................145

10.1. WHAT IS LOGISTIC COCKPIT (LC)?.......................................................14510.2. LOGISTIC COCKPIT FUNCTIONS..............................................................146

11 REPORTING AND ANALYSIS................................................................151

11.1. SAP BW BUSINESS EXPLORER...............................................................15111.2. WORKING WITH BEX.............................................................................15311.3. BEX ANALYZER.....................................................................................15911.4. RESTRICTED KEY FIGURES....................................................................16711.5. CALCULATED KEY FIGURES...................................................................17011.6. VARIABLES.............................................................................................17511.7. CONTENT VARIABLES............................................................................17911.8. EXCEPTIONS...........................................................................................18011.9. CREATING EXCEPTIONS..........................................................................18011.10. CONDITIONS...........................................................................................187

12 BEX WEB APPLICATION DESIGNER..................................................189

12.1. INTRODUCTION.......................................................................................18912.2. FEATURES...............................................................................................18912.3. Sample Web Dashboards.......................................................................196

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1 Introduction to Business Intelligence & Data

Warehousing1.1. Business Intelligence and Data Warehousing

Business Intelligence is a technology based on customer and profit oriented models that reduce operating costs and provide increased profitability by improving productivity, sales, and service and help to make decision-making capabilities at no time. Business Intelligence Models are based on multi dimensional analysis capabilities.

BI solutions differ from and add value to standard operational systems (OLTP systems – Online Transaction Processing systems) in three ways -

By providing the ability to extract, cleanse and aggregate data from multiple operational systems into a separate data mart or data warehouse

By storing data often in a star or multi dimensional cube format, to enable rapid delivery of summarized information and drill down to detail

By delivering personalized, relevant informational views and querying, reporting and analysis capabilities for gaining deeper business understanding and making better decisions faster

To implement BI, the following technologies are used- Data Marts/ Data Warehouses - A data warehouse is a subject

oriented, integrated, time variant, non-volatile collection of data in support of management's decision-making process. To facilitate data retrieval for multi dimensional analytical processing, a special database design technique called a star schema is used very often.

Extraction, Transformation and Loading (ETL) - Data is extracted from multiple source systems. Data is cleansed and transformed and into a consistent format and structure. The cleansed data is loaded into the data warehouse.

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On-Line Analytical Processing (OLAP) and Data Mining - Analysis tools are applied against the data warehouse to analyze and mine the data.

The main differences between an OLTP and an OLAP system are as follows –

Criteria OLTP data OLAP dataPurpose OLTP servers handle

mission critical production data accessed through simple queries.

OLAP servers handle management critical data accessed through an iterative analytical investigation.

Time Scale Organization’s day-to-day operational data. Current data.

Historical data for trend analysis.

Indexing Optimize update performance by minimizing the number of indexes.

Optimize ad hoc query performance by including lots of indexes.

Normalization

Fully normalized. Possibly partially denormalized for performance reasons.

Organization Organized around business functions.

Organized around information topics.

Values Typically coded data (e.g. product codes) for efficiency reasons.

Typically descriptive data (e.g. product names) for ease-of-use reasons.

Operations performed

Insert, Delete, Update. Read only.

Homogeneity Possibly scattered among a variety of databases, under a mix of DBMS and operating systems, and using different value coding schemes.

Centralized into a single homogeneous data store in the case of a data warehouse; or a collection of homogeneous subject-oriented data marts.

DBMS Chosen primarily for its ability to meet the organization's OLTP

Chosen primarily for its ability to meet the organization's OLAP

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needs. Usually an RDBMS.

needs. Usually a multi-dimensional database.

Table 1.1: Comparison of OLTP and OLAP Data

1.2. The Classic Star SchemaThe star schema derives its name from its graphical representation like a star. This database schema classifies two groups of data: facts (sales or quantity, for example) and dimension attributes (customer, time, and material, for example).

A fact is measure that answers the questions like “how much?” and “how many?” The fact data (values for the facts) are stored in a highly normalized fact table. A dimension is a textual description of the dimensions/features of the business. The dimension answers the questions “Who? What? When?” For example, the dimensions of a product may include product name, brand name, size, and packaging type. The values of the dimension attributes are stored in various demoralized dimension tables.

As shown in figure 1.1, a fact table appears in the middle of the graphic, along with several surrounding dimension tables. The central fact table is usually very large, measured in gigabytes. It is the table from which we retrieve the statistical data. The size of the dimension tables amounts to only 1 to 5 percent of the size of the fact table. Foreign keys tie the fact table to the dimension tables.

Figure 1.1: Classic Star Schema

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1.3. Introduction to SAP BWThe SAP Business Information Warehouse (SAP BW) is a state-of-the-art, end-to-end data warehouse solution developed by SAP. It enables users to analyze data from operative SAP applications as well as from other business applications and external data sources such as databases, online services and the Internet. SAP BW enables Online Analytical Processing (OLAP) for staging of information from large amounts of operative and historical data. SAP BW server is pre-configured for core areas and processes and allows users to examine the relationships in all areas of an organization.

With the Business Explorer (BEx), SAP BW gives a flexible reporting and analysis tool to support strategic analyses and decision-making processes within an organization. These tools include querying, reporting and OLAP functions.

1.4. SAP BW ArchitectureSAP BW architecture is made up of three functional layers.

Source Systems SAP BW Server SAP BW OLAP

Figure 1.2: SAP BW Three Layer Architecture

1.4.1. Source SystemsA source system is a reference system that functions as a data provider for SAP BW. SAP BW distinguishes between four kinds of source systems:

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1.4.1.1. MySAP.com Components SAP BW is fully integrated into the new mySAP.com world. SAP has provided a set of predefined extraction structures and programs, called DataSources, to extract the source data from mySAP.com components and then to load the data directly into SAP BW.A SAPI (Service Application Programming Interface) is an SAP-internal component that is delivered as of Basis release 3.1i. Communication between mySAP.com components and SAP BW takes place via this SAPI.

1.4.1.2. Non-SAP Systems The open architecture of SAP BW allows data to be extracted from heterogeneous sources across the organization thus making it possible to have consolidated data basis for reporting. SAP delivers various tools, which allow these interfaces to be implemented quickly and efficiently.

In heterogeneous system landscapes, an important requirement is that the different data structures and content are consolidated before being loaded into SAP BW. You can use an ETL tool such as Essential Data Stage to load data from heterogeneous systems, such as Siebel and PeopleSoft, transform this data into a single format and then load it via a Business Programming Interface into SAP BW. BAPI is the interface used for the structured communication between SAP BW and external systems. Both data providers and ETL tools use this interface.

SAP automatically supports automatic import of files in CSV or ASCII format for flat files as standard. The SOAP (Simple Object Access Protocol) RFC Service is used to read XML data and to store it in a delta queue in SAP BW. The data can then be processed further with a corresponding DataSources and SAPI.

1.4.1.3. Data Providers SAP BW can also be supplied with target-orientated data from various providers. For example, you can compare the market research data provided by an agency with your own operative data. Again, BAPI is used for the transfer of data supplied by the data providers to SAP BW.

1.4.1.4. Databases SAP BW allows data to be loaded from external relational database systems. A Data Source is generated based on the external table

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structure, enabling table content to be loaded quickly and consistently into SAP BW. DB Connect is a way, which allows relational databases to be accessed directly. Here, SAP DB MultiConnect is used to create a connection to the database management system (DBMS) in the external database. By importing metadata and original data, the necessary structures can be generated in SAP BW and the data can be loaded into the SAP BW system.

1.4.2. SAP BW ServerSAP BW server provides a 'Staging Engine', which controls the data loading process. It also features SAP BW databases, which store master, transaction and metadata.

The Administrator WorkBench (AWB) is responsible for the control, monitoring and maintenance of all data procurement processes. The Administrator WorkBench is the place where you define all relevant information objects, plan load processes using a scheduler, and monitor them using a monitor tool. However, before the data is in a suitable form to be stored, it must be prepared by the Extraction, Transformation and Load (ETL) process.

1.4.3. SAP BW OLAPThe Online Analytical Processing (OLAP) processor allows you to carry out multi-dimensional analyses of SAP BW data sets. It also provides the OLAP tools with data via the BAPI, XML/A or ODBO (OLE DB for OLAP) interfaces. In principle, the OLAP area can be divided into three components:

BEx Analyzer (Microsoft Excel based) BEx Web Application BEx Mobile Intelligence

You can use these tools to carry out both Microsoft Excel and Web-based analyses across several dimensions (such as time, place, product, and so on) simultaneously.

1.5. The SAP BW Star SchemaThe multi-dimensional model in SAP BW is based on the SAP BW star schema. SAP came up with the enhanced star schema to resolve the problems experienced with the classic star schema. Figure 1.3 shows the crossover between the classic star schema shown in the Figure 1.1 and the SAP BW star schema. For the time being, only components relevant to the modeling view are taken into consideration.

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Figure 1.3: SAP BW Star Schema

The main distinction between a classic start schema and SAP BW star schema is that in the SAP BW star schema the dimension tables do not contain master data information. This master data information is stored in separate tables, called master data tables. We can think of the SAP BW star schema as two self-contained areas:

InfoCube Master Data Tables/Surrogate ID (SID-) Tables

1.5.1. InfoCubeInfo Cubes are the central objects of the multi-dimensional model in SAP BW. Reports and analyses are based on these. From a reporting perspective, an InfoCube describes a self-contained data set within a business area, for which you can define queries.An InfoCube (Basis Cube) consists of a number of relational tables- a central fact table surrounded by several dimension tables- combined on a multi-dimensional basis.

Note: There are various types of InfoCube in BW, which will be discussed later. Till then an InfoCube will always refer to a Basis Cube. The Basis Cube is the InfoCube relevant for modeling, since only physical objects (objects that contain data) are considered in the modeling within the SAP BW- data model.

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Figure 1.4: InfoCube

In the SAP BW- star schema, the facts in the fact table are referred to as key figures and the dimension attributes as characteristics. The dimension tables are linked relationally with the central fact table by way of foreign or primary key relationships. In contrast to the classic star schema, the characteristic values are not stored in the dimension tables. A numerical SID key is generated for each characteristic. This foreign key replaces the characteristic as the component of the dimension table. Here, SID stands for Surrogate ID (replacement key). In the graphic above, these keys are given the prefix SID_. For example, 'SID_MATERIAL' is the SID key for the characteristic 'MATERIAL' ('MATERIAL_ID').

Each dimension table has a generated numerical 'primary key', called the dimension key. In the graphic above, this dimension key is denoted with the prefix DIM_ID_. Here, 'DIM_ID_MATERIAL' is the dimension key for the material dimension table.

As in the classic star schema, the primary key of the fact table is made up of dimension keys ('DIM_ID_DATENPAKET', 'DIM_ID_ZEIT', 'DIM_ID_EINHEIT', 'DIM_ID_KUNDE', 'DIM_ID_MATERIAL').

1.5.2. Master Data Tables/SID TablesAdditional information about characteristics is referred to as master data in the SAP BW. The master data is classified into three types:

Attributes Texts (External) hierarchies

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Master data information is stored in separate tables called master data tables (separately for attributes, texts and hierarchies). These tables are independent of the InfoCube. For example, as shown in the Figure 1.3, the attribute ‘material group’ is stored in the attribute table, the text description for 'material name' is stored in the text table and the material hierarchy is stored in the hierarchy table for the characteristic 'MATERIAL'. In this way, the characteristic 'MATERIAL' is the primary key for the master data tables belonging to this characteristic.

As mentioned earlier, precisely one numerical SID key is assigned to each characteristic. This assignment is made in a SID table for the respective characteristic, whereby the characteristic becomes the primary key in the SID table. As shown in the Figure 1.5, the SID key 'SID_MATERIAL' is assigned to the characteristic 'MATERIAL' in the SID table for characteristic 'MATERIAL'. The SID table is connected to the associated master data tables via the characteristic key.

Figure 1.5: Master Data Tables

1.5.3. Connecting Master Data Tables to an InfoCubeMaster data tables are connected to an InfoCube (and thus to the key figures of the fact table) by way of the SID tables. The following graphic illustrates this.

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Figure 1.6: Connecting Master Data Tables to InfoCube

The excavation of master data from the dimension tables using SID technology allows you to use the same master data with different Info Cubes. In other words, the master data is InfoCube-independent, and can be used by several Info Cubes at the same time.

Figure 1.7: Sharing Master Data Tables among InfoCubes

1.5.4. Comparison of SAP BW Star Schema and Classic Star Schema

Classic Start SAP BW Star Schema

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SchemaCube InfoCubeMeasure Key figure or KPIFact table Fact table(Dimension) Attribute

Characteristic Navigational attributes Display attributes (External) Hierarchy

nodeDimension (Table) Dimension table

Master table Text table External hierarchy

Table (SID) Table

NA Standard business contentNA HierarchiesNA MultiProvidersNA Remote cubes

Table 1.2: Comparison of SAP BW Star Schema and Classic Star Schema

1.5.5. Advantages of the SAP BW Star SchemaThe use of automatically generated INT4 keys (SID keys, DIMID keys) enables faster access to data than via long alphanumeric keys. Thanks to the excavation of master data from the dimension tables using the SID technique, the following modeling possibilities exist:

Historizing dimensions Multi-lingual capability Cross-InfoCube use of master data ("shared

dimensions") The query performance is improved here, as aggregated

key figures can be stored in their own fact tables.

1.5.6. Disadvantages of the SAP BW Star SchemaA large number of joining operations take place due to introduction of various tables. This could slow down the data access operations as compared to the classic star schema.

1.5.7. SAP BW Star Schema RestrictionsTo summarize the features of SAP BW Star Schema, remember the following points.

Maximum of 1 fact table per InfoCube Maximum of up to 16 dimension tables (containing different

characteristics) per InfoCube

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Minimum of 4 dimension tables (3 system reserved plus at least 1 user defined) per InfoCube

Maximum of 248 characteristics per dimension table Maximum of 233 key figures per InfoCube The SAP BW star schema does not contain master data,

hierarchy, or texts (these data are stored outside of the star schema and are readily available for querying).

1.6. Introduction to Data Warehousing Workbench:

The Data Warehousing Workbench (DWB) is the central tool for performing the tasks in the data warehousing process. It provides data modeling functions as well as functions for control, monitoring and maintenance of all processes in SAP NetWeaver BI having to do with data procurement, data retention, and data processing.

Functional Areas of the Data Warehousing Workbench: Modeling Administration Transport connection Documents Business Content Translation Metadata Repository

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Figure 1.8: Data Warehousing Workbench

1.6.1. ModelingThe Modeling function area is used to create and maintain (Meta) objects relevant to the data staging process in SAP BW. These objects are displayed in a tree structure, in which the objects are ordered according to hierarchical criteria. You can use a context menu (using the Right mouse click) to access the relevant maintenance dialogs for each object in the object tree. You can also carry out additional functions. To access the Modeling function area, choose transaction RSA1.

1.6.2. AdministrationIn the Modeling and Administration functional areas is used to display the navigational area and, if applicable, the corresponding object tree in the left hand area of the screen when applications are called. This means that you can use the tree to start new application you are in.

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1.6.3. Transport ConnectionThe Transport Connection can be used to collect newly created or changed objects in the SAP BW system. You can use the Change and Transport Organizer (CTO) to transport them into other SAP BW systems. (From quality assurance into the productive system, for example). To access the Transport Connection function area, in the AWB navigation window, choose Transport Connection.

1.6.4. DocumentsThe Documents function area enables you to insert, search in, and create links for one or more documents in various formats, versions and languages for SAP BW objects. To access the Documents function area, in the AWB navigation window, choose Documents.

1.6.5. BI ContentBI Content provides pre-configured information models based on metadata. It provides users in an enterprise with a selection of information they can use to fulfill their tasks. To access the BI Content function area, choose the transaction RSORBCT.

1.6.6. TranslationIn the Translation function area, you can translate short and long texts belonging to SAP BW- objects. To access the Translation function area, in the AWB navigation window, choose Translation.

1.6.7. Metadata RepositoryIn the HTML-based SAP BW- Metadata Repository, all SAP BW Meta objects and the corresponding links to each other are managed centrally. Together with an integrated Metadata Repository browser, a search function is available enabling a quick access to the Meta objects. In addition, metadata can also be exchanged between different systems, HTML pages can be exported, and graphics for the objects can be displayed.To access the Metadata Repository function area, choose the transaction RSOR.

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2 Introduction to InfoObjects & Info Cubes

2.1. Introduction to InfoObjectsInfoObjects in SAP BW are the smallest available information modules or fields. They contain the technical and specialist information for master and transaction data in SAP BW. InfoObjects are part of the Metadata Repository. They are uniquely identified with their technical name. InfoObjects are the basic components of the SAP BW star schema. An Info Object is a generic term for SAP BW business evaluation objects. InfoObjects are part of the SAP BW metadata repository. They describe the properties (technical definition and business logic) of the application field.

SAP provides various InfoObjects as a part of its Business Content. The technical names of these InfoObjects begin with 0. In addition to these standard InfoObjects, we can define our own InfoObjects.

2.2. Types of InfoObjectsThe InfoObjects are divided into 2 types viz.

Characteristics Time Characteristics Units Technical Characteristics

Key figures

1. Characteristics: In SAP-BW, attributes located in the dimension tables are called Characteristics. In traditionally data modeling, a characteristic is a field that allows activity to be categorized such as customer, customer group, material, material group, product, product group, sales organization, fiscal year, period, and region. Characteristics correspond to key fields in a fact table and can be used to sort, select, and subtotal in queries. Note that characteristics are descriptive in nature and are not normally additive as opposed to key figures. SAP BW offers four possible data types for characteristics:

1. CHAR (character)2. NUMC (Numeric Character)3. DATS (Date)4. TIMS (time)

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Note: There can be up to 248 characteristics per dimension table The length of the characteristic value can vary from 1 to 60 Characteristic may have a compound key and can refer to

other characteristics

2. Key Figures (quantitative information, e.g., amount, count, quantity)

Note: Key figure InfoObjects cannot be authorization relevant.

Key Figures – A key figure is a data element from a fact table and usually represents numeric data that can be measured, such as revenues and gross profit. The key figure InfoObjects provide the values to be evaluated. E.g. Quantity sold (0QUANTITY), Amount (0AMOUNT), Headcount etc. In other words, they represent the facts in the conventional data warehouse.

Characteristics - Characteristic InfoObjects are business reference objects, which are used to analyze key figures E.g. Plant (0PLANT), Country (0COUNTRY), Material (0MATERIAL), and Product (MYPRODUCT). Characteristics provide different views for analyzing the facts. The dimensions are formed using Characteristic InfoObjects.

Time Characteristics - Time characteristics form the time reference frame for data analyses and evaluations. They are delivered with Business Content. It is not possible to define your own time characteristics. Some of the time characteristics available are Calendar Day (0CALDAY), Calendar Month (0CALMONTH), Calendar Year (0CALYEAR), and Fiscal Year (0FISCYEAR).

Units - The Unit InfoObjects enable key figure values to be associated with their corresponding units in evaluation. E.g. Currency unit (0CURRENCY) can be associated with the key figure Amount (0AMOUNT) and value unit (0UNIT) with Quantity (0QUANTITY).

Technical Characteristics - These characteristics are used for SAP BW’s internal operations. E.g. Request ID (0REQUID) represents the numbers allocated to loading requests while Change ID (0CHNGID) give the numbers allocated by the system during ‘aggregate change runs’.

InfoObjects can exist in three versions in SAP BW:

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D: SAP-delivered version. SAP-delivered (D) InfoObjects are reserved SAP objects. They can be used as templates or copy in the active SAP BW client.

M: Revised version. Revised (maintenance) version (M) is for objects that are under revision. They could be a copy of an SAP-delivered InfoObjects under an active SAP BW client or a new Info Object being defined by the customer. Before they can be used, revised objects have to be transferred to an active object and then activated.

A: Active version. Active (A) InfoObjects are InfoObjects that meet all specified rules and are ready for use in the SAP BW active client.

Activation is a process that makes revised objects available at runtime. Upon activation a runtime object is generated and can be accessed by application programs and screen templates.

In SAP BW, all dependent objects need to be activated before they can be used, including InfoObjects, InfoCubes, transfer rules, communication structures, and so forth. Additionally, custom InfoObjects can be created (e.g., to define a custom data file).

InfoObjects are organized in two areas of the SAP BW Administrator Workbench (AWB):

1. Info Area. An Info Area is a folder in the AWB used to store and organize related InfoObjects.

2. Info Object Catalog. An Info Object catalog is a folder in the AWB containing related InfoObjects.

There are two types of InfoObjects catalogs:1. Characteristics2. Key Figures

2.3. Characteristic InfoObjectsAs mentioned earlier, the characteristics InfoObjects are the business reference objects using which we analyze the facts. While creating such characteristics in SAP BW, the following tab pages are available in the maintenance menu.

General Business Explorer Master data/texts Attributes

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Hierarchy Compounding

You can use these tab pages to define characteristic InfoObjects and change their settings. A precise knowledge of the business significance of these characteristics is required before you can define them in a meaningful way.

GeneralThis tab page is used to determine the basic properties of a characteristic, for example description, data type (CHAR, NUMC, DATS or TIMS), length (max. 60 Characters in case of CHAR or NUMC) and conversion routine (E.g. ALPHA, MATN1).

Note: When defining a characteristic, you must enter at least a description, data type and length. All other settings on this and other tab pages are optional.

Figure 2.1: Creating Characteristic InfoObjects – General

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Note: If the Attribute Only check box under miscellaneous block is selected, the attribute can be used only as a display attribute, not as a navigational attribute. Selecting this option also allows you to select the Lowercase letters. If the option Lowercase letters is selected, the attribute can accept lowercase letters in data to be loaded. If the option Lowercase letters is selected no master data tables, text tables, or another level of attributes underneath are allowed

Business Explorer (BEx)This tab page is used to set the display defaults during reporting in the Business Explorer (BEx). For example, you can set the default as to the characteristic to appear as a textual description or as only the key value or both in BEx.

SAP Business Explorer also allows displaying the data on maps (World map, Continent maps etc.). Some third party vendors like ESRI, provide special type of files called as Shape files that serve as a basis for displaying BW data on maps. The related settings can be done using the BEx tab.

Figure 2.2: Creating Characteristic InfoObjects – Business Explorer

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Master data/textsOn this tab page, you determine whether or not the characteristic can have attributes or texts. If the characteristic is to have its own texts, you need to make at least one text selection (short, medium-length, long text- 20, 40, 60 characters). The attributes are assigned to the characteristic on the Attributes tab page.

Figure 2.3: Creating Characteristic InfoObject – Master data / texts

AttributesAttributes are themselves InfoObjects (characteristics/key figures) that are used to describe characteristics in greater detail. For example, the characteristic Customer Number can be described in more detail with other InfoObjects like Customer Type and Customer Class, Address etc. If the With master data indicator was set on the Master data/texts tab page you are able to specify attributes and properties for these attributes together with the characteristic on the Attributes tab page.

Figure 2.4: Creating Characteristic InfoObject – Attributes

Attributes can be of 2 types – Display Attributes or Navigation Attributes.

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Display Attributes - Display attributes can only be used as additional information in reporting when combined with the characteristic. In other words, in reporting, you cannot navigate within the dataset of a data target (InfoCube or ODS object).

Navigation Attributes - Navigation attributes allow the users to navigate in reporting. When a query is executed, the system does not distinguish between navigation attributes and characteristics for a data target (InfoCube or ODS object). In other words, all navigation functions in the query are also possible for navigation attributes. In order to make these attributes available as navigation attributes in reporting, you need to activate them once more on a data target (InfoCube or ODS object) level. Otherwise, the attributes function as display attributes.

A characteristic that is used as a navigation attribute can also have its own navigation attributes. These are called transitive attributes (navigation attributes with two levels). You can activate these as well, thus making them available for reporting.

Example: The characteristic Info Object "cost center" has the navigation attribute "company code" (amongst others). In turn, this characteristic has the navigation attribute "company". In this case, "company" is a transitive attribute that you could activate as navigation attribute.

Note: If a characteristic InfoObjects is defined as Attribute Only, you

can only use this characteristic InfoObjects as a display attribute for another characteristic.

The extensive use of navigation attributes leads to a large number of tables and joins, which can reduce performance.

Time Dependent AttributesSwitch attributes (display or navigation attributes) to 'time-dependent' if a validity area is required for each attribute value.

(External) HierarchyHierarchies are used in analysis to describe alternative views of the data. A hierarchy comprises of multiple nodes and leaves. The nodes stand in a parent-child relationship and the hierarchy leaves are represented by the characteristic values. On the Hierarchy tab page, you determine whether or not the characteristic can have hierarchies, and if so, what properties these hierarchies are allowed to have. If the ‘With hierarchies’ indicator is set, hierarchies can be

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created for this characteristic within SAP BW (choose transaction RSH1). Alternatively, they can be loaded from SAP R/3 or flat files.

SAP BW has a unique hierarchy implementation. Hierarchies are tree-like structures on characteristic’s domain (e.g., ship to and bill to). In SAP BW, hierarchies are a type of master data.

Key benefits of the SAP BW implementation of hierarchies are that:

Hierarchies are stored in a class of master data tables (/H***), which are similar to master data and can therefore be used and referenced in all of the InfoCubes within an SAP BW instance.

You can define multiple hierarchies against one single characteristic.

SAP BW supports multiple versions of a hierarchy, and internal and external hierarchies.

Remarks:Changes for hierarchies are available only after the “data change aggregate update” program has been run. This is true even if there are no aggregates associated with the hierarchies.

When using hierarchies you should filter out the ‘Not assigned’ node in the hierarchy. Often the user does not notice that all nodes are included in the output (even the ones that are not needed or blank), but it slows down the query result because a lot of useless data is being selected.

A hierarchy can be created using three methods:

1. Import from flat file2. Manual creation in BW3. Import from SAP R/3 (preferred option)

Two components of interest for hierarchies are: Leaves. A leaf is a characteristic value and represents the

last level of a hierarchy. The SID value for a leave is a positive random integer.

Node. A node is a set of leaves in a hierarchy. The SID value for a node is a negative random integer.

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Figure 2.5: Creating Characteristic InfoObject - Hierarchy

A Version-Dependant HierarchyHierarchies for a characteristic can be maintained in different versions. These versions can then be compared with one another in a query. E.g. As shown in the Table 2.1, District 2 is placed under North region in the planned version but is under South region in the actual version.

Hierarchy Version PLAN

Hierarchy version ACTUAL

Region NORTH Region NORTHDistrict 1 District 1District 2 District 3District 3

Region SOUTH Region SOUTHDistrict 4 District 2

District 4Table 2.1: Version-dependant Hierarchy

A Time-Dependent Entire Hierarchy

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You determine here whether the entire hierarchy is allowed to be time-dependent. In other words, there are versions for this hierarchy that is valid for a specific time interval. The system automatically chooses the valid version.

Hierarchy 01.01.2000 – 31.12.2005

Hierarchy 01.01.2006 – 31.12.2009

Region NORTH Region NORTHDistrict 1 District 1District 2 District 3District 3

Region SOUTH Region SOUTHDistrict 4 District 2

District 4Table 2.2: Time-dependant Entire Hierarchy

Example: During restructuring of an organization's sales districts for the District characteristic, the hierarchy is made time-dependent. This enables this restructuring to be compared for different times in a query.

Time-Dependent Hierarchy StructureYou determine here whether or not the hierarchy structure (a hierarchy node) is to be time-dependent. The hierarchy is then constructed for the current key date or for the key date specified in the query.

Example: During restructuring of an organization's sales districts, it was found that an employee is assigned to different cost centers at different times.

Time-Dependent Hierarchy Structure for Char. 'Cost Center'

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Figure 2.6: Time-Dependent Hierarchy Structure for Char. 'Cost Center'

Hierarchy IntervalsIt is possible to position characteristic values in the form of intervals under a hierarchy node. Instead of positioning each cost element value for material costs under the material costs node individually in a cost element hierarchy, you can specify the cost element values as a cost element between 100 and 1000. You can also create intervals for characteristic values, for which no master data exists. As a result, you can save yourself the need to extend the hierarchy every time for new master data.

Note: You cannot create hierarchies for characteristics that

are referenced to other characteristics (Reference characteristic).

A characteristic can have more than one hierarchy. If a characteristic is to have hierarchies; the maximum

length (of the characteristic value) with compounding is restricted to 32 instead of 60 characters.

Hierarchies can have a maximum of 98 levels.

Reverse +/ - signs for hierarchy nodesThis function can be used to influence the display behavior of nodes in the query. For each hierarchy node, you can specify whether the +/ - sign for the transaction data posted on this node is to be reversed or not in the query display.

CompoundingIn Compounding, a field or another object is attached to an Info Object. A compounding characteristic is when the object’s definition is incomplete without the definition of another characteristic. In other words the meaning of master data depends on the source of the data.

On this tab page, you determine whether or not the characteristic is to be compounded to other InfoObjects. You often need to "compound" characteristic values to enable characteristic values to be assigned uniquely.

Example: Cost center 100 stands for sales and distribution in controlling area 1000, and it also stands for sales in controlling area 2000. In this

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case, you would define a "cost center" to "controlling area" characteristic compounding.

In addition, compounding can be used to define dependencies between objects. This simplifies navigation in reporting.

Figure 2.7: Creating Characteristic InfoObjects - Compounding

Note - Performance can be affected when "compounded" characteristics are used extensively, particularly when a large number of characteristics are included in a compounding. Compound attributes requires overhead, so you should not use them unless it is absolutely necessary.

Some examples of compounding are:CO. Cost center has a compound object controlling area.MM. Storage location has a compound object plant.

A compound field is similar to a superior organizational field in SAP R/3.

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2.4. Creating a Characteristic in the Info Object Tree

1. In the initial screen of the Data Warehousing Workbench, choose the function area Modeling InfoObjects.

2. Create/maintain an Info Area

Info Area constitutes the uppermost evaluation criteria in the Info Object and data target tree. The Info Object tree contains Info Areas beneath the initial InfoObjects node. Under an Info Area node, you can find more Info Areas or Info Object catalogs. You can create an Info Area via the context menu for the initial node, or using an Info Area already in the system.

3. Create/maintain an Info Object Catalog with type characteristic.

Info Object Catalogs are used to group InfoObjects together to provide both a better overview of them and to arrange them logically according to application-specific perspectives. An Info Object Catalog has the type characteristic or key figure. Under an Info Object Catalog, there are either characteristics/units/time characteristics or Info Object tree key figures. An Info Object Catalog is created via the context menu for an Info Area.

4. Choose Create Info Object via the context menu for the Info

Object Catalog.

5. Enter a technical name (3-9 characteristics) and long description for the characteristic (either a reference characteristic or a template characteristic) and confirm your entries.

If you choose a "template characteristic", the "new" characteristic assumes this characteristic's properties, which you can then edit. If you choose "reference characteristic", the "new" characteristic assumes all of this characteristic's technical properties (data type, length, master data, conversion routine, number of type of "compounded" characteristics, for example). It also assumes its business texts (descriptions, display, text selection and person responsible for example). Nevertheless, technical properties can only be changed in the reference characteristic.

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6. Maintain the tab pages General Business Explorer Master data/texts Hierarchy Attributes Compounding

When defining a characteristic, you need to enter at least the description, data type and length. All other settings on the General and other tab pages are optional.

7. Save and activate the “new” characteristic.

Activating the characteristic generates the objects in the Data Dictionary (DDIC) that belong to it. These include the data element, domain and master data tables for attributes/ texts/hierarchies. If attributes, texts or hierarchies, or a combination there of are assigned to the characteristic, this characteristic is called a Master data-carrying characteristic. A characteristic is a SAP BW object that physically contains data in the appropriate tables (master data and SID tables). Objects with these properties are called data targets in SAP BW. In the same way, a characteristic can also be an InfoProvider. Objects are called Info providers in SAP BW when queries based on them can be defined/ executed.

Figure 2.8: SID Tables

Transactions RSD1 and RSD5 allow you to create InfoObjects without assigning them to an InfoObject Catalog. Such InfoObjects are called as "free" InfoObjects. These InfoObjects are then

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assigned to the InfoObject Catalog CHANOTASSIGNED (non-assigned characteristic) or KEYNOTASSIGNED (non-assigned key figure) depending on the type, under the Info Area NODESNOTCONNECTED (non-assigned nodes). However, these InfoObjects can be assigned to an InfoObject Catalog at any time. When an InfoObject Catalog is deleted, the InfoObjects assigned to it are not deleted along with it. Instead, the non-assigned characteristic or non-assigned key figures are assigned to the appropriate InfoObject Catalog.

2.5. Key FiguresAs we know, the key figure InfoObjects represents the business facts such as quantity, amount, and count and so on. The following tab pages are available in the maintenance menu, with which you can define key figure InfoObjects and change settings.

Type/Unit Aggregation Additional Properties

2.5.1. Type/UnitOn this tab page, you determine the key figure type (amount, quantity, number etc.), the data type (currency field / floating point number, quantity field/ floating point number etc.) as well as the currency / quantity unit.

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Figure 2.9: Creating Key Figure InfoObject – Type/Unit

For the key figure types amount, quantity and number, you can choose between the data type’s decimal number and floating-point number. For the date and time key figure types, you can choose the decimal display if these fields are to be included in the calculation. If you choose the amount or quantity key figure type, you must assign a currency or quantity unit to this key figure. For the key figure type amount, you can choose between a fixed currency (EUR, for example) and a variable currency, (OCURRENCY) for example. For the key figure type quantity, you can choose between a fixed quantity unit, KG for example, or a variable quantity unit, OUNIT for example.

2.5.2. AggregationDefault BEx settings for aggregation of the key figure are done using this tab page. This is required for the meaningful evaluation of the key figure. The aggregation behavior determines whether or not, and in which way, the key figure values can be summarized using the different characteristics/their values within the evaluation.

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Figure 2.10: Creating Key Figure InfoObject – Aggregation

2.5.3. AggregationIn this field, you specify the function (SUM/MAX/MIN) which determines the way in which the key figure is aggregated "by default" for the same key (-->standard aggregation behavior).

2.5.3.1. Exception Aggregation In this field, you specify the function (last value, first value, max, min...) which determines the way in which the key figure is aggregated using the reference characteristic for exception aggregation in the Business Explorer.

2.5.3.2. Reference Characteristic for Exception Aggregation

In this field, you choose the characteristic, with reference to which the key figure is aggregated with exception aggregation. Generally this is a time characteristic. However, it can be any characteristic.

Example:The key figure number of employees is aggregated using the characteristic cost center ( Standard aggregation behavior). In

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this case, you would set a time characteristic as a reference characteristic with last value as the exception aggregation.

2.5.3.3. Cumulative/Non-cumulative Values Cumulative values (revenue, for example) are key figures for which key figure values must be posted in every time unit that is being reported on (time period-specific values).

Non-cumulative values (warehouse stock, for example) are key figures that are only evaluated for selected time periods (markers).The values for the remaining periods are calculated from the value in a marker and the non-cumulative changes (in-/out- flow) that lie in between.

There are two ways of defining non-cumulative values:

Non-cumulative with Non-Cumulative Value ChangeWhen defining the non-cumulative value, a cumulative value is also required as a key figure InfoObject (non-cumulative value change). This must agree with the non-cumulative value to be defined in the type definition.

Non-cumulative with In- and Out-flowWhen defining the non-cumulative value, two cumulative values, "inflow" and “outflow” are required. These must agree with the non-cumulative value to be defined in the type definition.

Note: Non-cumulative values always have summation as their default aggregation. For time characteristics, they have an exception aggregation other than summation. On the other hand, cumulatives using all characteristics - in other words, including time characteristics- have the aggregation summation.

The cumulative non-cumulative value change, inflow and outflow must have summation as their default- and exception aggregation. To optimize the data transport and handling for non-cumulative values in SAP BW, non-cumulative values are handled differently to cumulative values. This also applies for technical data transfer and –storage. There are no differences in the way cumulative- and non-cumulative values are handled in reporting.

2.5.4. Additional PropertiesThis tab page is mostly used to change default settings for the key figure display type (number of decimal places, display scaling and so on) in BEx.

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Figure 2.11: Creating Key Figure InfoObject - Additional Properties

As with a characteristic, you are able to define a key figure as Attribute Only, meaning that the key figure can only be used as a display attribute for a characteristic.

2.5.5. Creating a Key Figure in the InfoObject Tree1. In the initial screen of the AWB, choose the function area

Modeling InfoObjects2. Create/Maintain an InfoArea within the InfoObject tree3. Create / Maintain an InfoObject Catalog with type key figure

within the InfoArea4. Choose Create InfoObject form the context menu of the

InfoObjectCatalog.

Enter the technical name (3-9 characters) and a long description for the key figure (either a reference key figure or a template key figure) and confirm your entry. (You need a reference

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characteristic for an ‘Elimination of Internal Business Volume’ in the query.)

5. Maintain the tab pages Type / Unit Aggregation Additional Properties

(If a key figure is defined with a reference, the additional tab page Elimination also appears.)

6. Save and activate the key figure

Activating the key figure generates corresponding DDIC objects. As mentioned above, if a key figure is defined with a reference, the additional tab page Elimination appears in the InfoObject maintenance. On this tab page, one or more characteristic pairs are specified, with reference to which the key figure can be eliminated upon execution of a BEx query. The characteristics in the pair must have the same reference characteristic. Instead of a characteristic you may also use a navigation attribute. A typical example of such a pair would be “sending Cost center”(0SEND_CCTR) and “receiving Cost center”(0RECV_CCTR).

2.6. InfoCubesA cube is synonymous with a star schema, which means it consists of a fact table and a surrounding group of dimension tables, all of which contain data that logically belong together, and are linked relationally. Cubes are the central objects, upon which reports and analyses are based in multidimensional modeling. InfoCubes are the central objects of the multi-dimensional model in SAP BW. Reports and analyses are based on these. An InfoCube describes a self-enclosed data set for a business area from a reporting perspective. Queries can be defined and/ or executed on the basis of an InfoCube. InfoCubes contain the transaction data in multidimensional format. In SAP BW a cube is called an InfoCube.

There are following InfoCube types in SAP BW: Basis Cube (star schema). Combination of 1 fact table and

up to 16 dimension tables (standard InfoCube)

MultiProvider. Joining of several Basic and/or Remote Cubes (special implementation of the join of one or more basic InfoCubes)

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Demo Cube. SAP-supplied InfoCube (as part of the business content) to enable a complete data warehouse scenario to be implemented for demonstration and evaluation purposes (prepackaged intellectual capital)

Remote Cube. InfoCube whose transaction data are not managed in SAP BW but managed in a remote system (to access remote OLTP systems)

Only BasisCube physically contain data in the database. By doing so, they are also data targets. In contrast, Virtual Cubes only represent logical views of a dataset. There is no difference between these InfoCube types as far as the reporting end user is concerned. Queries can be defined based on all the above InfoCube types. InfoCubes are thus Info Provider’s.

Physical Data Stores: Basic Cubes InfoObjects (characteristics with attributes or texts) ODS objects that have the indicator for BEx reporting

Virtual Data Stores: Info Sets Remote Cubes SAP Remote Cubes Multi-Providers

2.7. BasisCubeAs already mentioned, a BasisCube consists of a quantity of relational tables arranged together in a star schema.

. Fact tableA BasisCube consists of one fact table, in which key figure values are stored. A fact table can contain a maximum of 233 key figures.

Facts and Key FiguresThe star schema is based on facts and fact tables. Facts are data elements from a fact table.

FactA fact is a measure that is normally (cumulative) and answers the question “how much?” or “how many?” A fact is referred to as a key figure in the SAP BW extended star schema. Revenues and expenses are examples of typical facts. Examples of non-cumulative

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facts include closing stock price, daily movements, or inventory levels.

A factless fact is an artificial fact and does not represent a numerical measurement. Factless facts are used as a counter to record a large number of events (e.g., daily class attendance).

Fact TableFacts, of course, reside in a fact table. A fact table is the central table in a star schema. It contains key figures and dimension IDs that point to the dimension tables. In a star schema, typically

The fact table is very large with small dimension tables. The fact table has a relatively small number of columns

(key figures) and a large number of rows (records) where associated dimension tables tend to have a large number of columns (attributes) and small number of rows.

Dimensions and CharacteristicsThe dimensions and characteristics are key components of a multidimensional model/star schema. The dimensions represent the points in the star. DimensionA dimension is a textual description of the dimensions/features of the business. The dimension answers the questions “who? what? when?” For example, the dimensions of a product may include product name, brand name, size, and packaging type. Dimensions are stored in dimension tables. The term dimension refers to dimension tables, and characteristics will be used as the content of dimension tables.

As a value added to other data warehouses, SAP has predefined three dimensions, time, unit and package, as reserved dimensions for the InfoCubes in SAP BW.

It is important to note that the SAP BW InfoCube/star schema is limited to a minimum of 4 and a maximum of 16 dimension tables:

A BasisCube usually has four dimension tables also called Reserved Dimension.

1. Units dimension table – This dimension exists if at least one key figure is of type ‘amount’ or ‘quantity’. Key figures of type Unit need to access the Unit dimension table during queries, which may cause degradation in system performance. Therefore, for query performance, key figure InfoObjects of

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type Number or Integer should be used whenever possible (unless you really plan to do currency/unit conversions in the queries).

2. Data package dimension table – This dimension is always present in a BasisCube. To identify discrete packets of information loaded into the InfoCube (this is needed to delete, reload, or maintain packets individually)

3. Time dimension Table - This dimension is always present in a BasisCube. Holds the time characteristics needed for analysis

4. A user-defined dimension for example material dimension table

It is important to note that the SAP BW InfoCube/star schema is limited to a minimum of 4 and a maximum of 16 dimension tables:

Three standard/reserved dimensions (time, packet ID, and unit)

At least one dimension to be defined by the SAP BW administrator

The SAP BW system administrator can create up to 13 dimension tables (computed by 16 – 3 reserved).

Figure 2.12: Structure of a BasisCube

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DimensionsA dimension in SAP BW is nothing but a grouping of logically related characteristics under a single umbrella term. A maximum of 248 characteristics can be combined within a dimension.

Line Item Dimension Characteristics can be defined as line items. In other words, aside from this characteristic, no other characteristics can be assigned to a dimension. This kind of dimension is called a line item dimension (degenerated dimension). This option is used when a characteristic has a large number of values (order number, for example), which, in combination with other characteristics, would lead to a large increase in dimension tables for the fact table, detrimentally affecting query performance.Figure 2.11 shows how the line item dimension does not have any dimension tables, in contrast to the normal dimension. In this case, the SID table of the line item is directly connected to the fact table by way of the external primary key relationships.

Figure 2.13: Line Item Dimension

Remote CubeA Remote Cube is also called a Virtual Cube. It is an InfoCube whose transaction data are not managed in SAP BW but in a remote system.

Benefits of Remote Cubes are: They do not store data in SAP BW. Only the structure of the Remote Cube is defined in SAP BW.

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Remote cubes are SAP’s alternative to OLTP reporting tools in SAP BW.

There are two types of Remote Cubes in SAP BW:

SAP Remote Cubes. The SAP Remote Cube is a Remote Cube that allows the definition of queries with direct access to transaction data in other SAP systems.

General Remote Cubes. A general Remote Cube is a Remote Cube that allows the definition of queries with direct access to transaction data in source systems other than SAP.

2.8. Creating an InfoCube in the InfoProvider Tree

1. In the-initial screen of the Data Warehousing Workbench, choose the function area Modeling InfoProvider.

2. Create/maintain an InfoArea within the InfoProvider tree3. Via the context menu (Right mouse click) for the InfoArea,

choose Create InfoCube4. Select either Standard or Real Time as the InfoCube type.5. Specify a technical name (3-9 characters) and a description

for the InfoCube/Template InfoCube.6. Select Create. If you want to create a copy of an already

existing InfoCube, you can enter an InfoCube as a template. The Edit InfoCube screen appears.

7. Transferring InfoObjects: On the left side of the screen, there are various templates

to choose from. These allow you to get a better overview in relation to a particular task. For performance reasons, the default setting is an empty template. Using the pushbuttons, select an InfoSource (only the InfoObjects for the communication structure of the InfoSource are displayed), an InfoCube, a DataStore object, or an InfoObject catalog.

The InfoObjects that are to be added to the InfoCube are divided into the categories characteristic, time characteristic, key figure and unit. You have to transfer at least one InfoObject from each category.

On the right side of the screen, you define the InfoCube. Using the Drag&Drop function, assign the InfoObjects in the dimensions and the Key Figures folder. It is possible to select several InfoObjects at once. You can also transfer entire dimensions using Drag&Drop. The system assigns

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navigation attributes automatically. These navigation attributes can be switched on for reporting in BEx.

Or:You can insert InfoObjects without selecting a template in the left half of the screen. This is useful if you know exactly which InfoObjects you want to include in the InfoCube. Choose Insert InfoObjects in the context menu for the folders for dimensions or key figures. In the dialog box that appears, you can enter and transfer up to ten InfoObjects directly, or you can select them using input help. You can use Drag&Drop to reassign them.

Figure 2.14: Characteristics for Cube8. Create dimensions: The dimensions data package, time, and

unit are available as the default setting. The data package dimension contains technical characteristics. Time characteristics and units are automatically assigned to the corresponding dimensions. In the context menu of the Dimensions folder, you can create additional dimensions under Create New Dimensions.

Figure 2.17: Defining Dimensions for a Cube

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Note: You can mark a dimension as a line item dimension. In addition, you can also set the Card. Height indicator to indicate high cardinality. This is used if the dimension has at least 10-20% the size of the fat table in terms of number of records. In this case, B tree indices are created instead of bitmap indices.

9. For better performance, partition the InfoCube using Extra Partitioning menu.

The number of partitions depends upon the span of time for which the data is stored in the InfoCube and the actual volume of data. E.g. As shown in the Figure 2.17, out of total 62 partitions, 60 partitions correspond to months ranging from January’2001 to December’2005. One partition is for the transaction data before January’2001 and one is for the data after December’2005.

Figure 2.18: Partitioning a CubeNote:

Partitioning of the fact table is limited to 0CALMONTH or 0FISCPER.

After partitioning, physically there will be more than one fact table.

Partitioning should be set up on creation of the InfoCube and occur after data have been loaded (partitioning can occur if data are in the InfoCube by using “Repartition” option.)

10. Save and activate the new InfoCube.

Upon activation of a BasisCube the corresponding DDIC objects like dimension tables, fact table (F table, E table) are generated. Thus the star schema gets technically realized.

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Note: Except for the text table, hierarchy table and E tables, you can view the various tables generated using the transaction LISTSCHEMA.

Note: A transactional InfoCube is a special BasisCube, especially developed for Strategic Enterprise Management (SAP SEM). The system accesses data in such a cube transactionally, in other words, data is written to the InfoCube (possibly from more than one user at the same time) and instantly read again when required. Standard BasisCubes are not suitable here. Use Standard BasisCubes for pure read access (when reading reference data, for example).

2.9. Technical Implementation of SAP BW Star Schema

As mentioned earlier, upon activation of InfoObjects and InfoCubes a number of DDIC objects- mainly tables and views - get generated. These DDIC objects are the way in which the SAP BW data model is realized technically.

2.9.1. Master Data TablesWhen a master data-carrying characteristic is activated, master data tables (attributes, text, hierarchies) are generated in the characteristic maintenance depending on the settings in the respective tab strip. In multidimensional data modeling, master data are not part of the model. They exist outside of the multidimensional structure. In SAP BW extended star schema, the master data are share across InfoCubes, which provides for consistency of master data across InfoCubes.

2.9.2. Text TableA text table is created if the ‘With texts’ checkbox is flagged prior to the creation and subsequent activation of the InfoObject. You can select the following properties here: (refer to Figure 2.18)

Short text Medium-length text Long text Texts are language-dependent Texts are time-dependent

The selection options affect the text table key. For example, in a time-dependent and language dependent text table, the two fields LANGU (language key) and DATETO (date valid to) belong to the text table key. Only one text table is generated for each characteristic.

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Figure 2.19: With Texts

The graphic shows the structure of the text table, for characteristic COSTC##: in this example. Since the indicators for short text, medium-length text, time and language-dependence were set on the Master data/texts tab page, these fields are included in the structure of the text table.

Legend:{...} "Compounded" characteristic/BIC/<...> Newly-created characteristicLANGU Language keyDATETO Date valid toDATEFROM Date valid from

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TXTSH Short description (20 characters)TXTMD Medium-Iength description (40 characters)TXTLG Long text description (60 characters)

Figure 2.20: Time-dependant Texts

Naming conventions in the text table:

/BIC/f<name of characteristic> (for customer-defined characteristics)/BI0/T<name of characteristic> (for SAP standard characteristics)

2.9.3. Attribute TablesIf you have not deselected the indicator in the ‘With master data’ checkbox (the checkbox is checked by default) on the Master Data/texts tab page, you can maintain attributes for the master data-carrying characteristics on the Attributes tab page. You can choose to define display attributes and navigation attributes as either time-dependent or time-independent. In this section, we only look at display attributes in greater detail. A maximum of two attribute tables can be generated for display attributes (time-dependent and time-independent attributes) for each master data-carrying characteristic.

Providing that one of either the P or Q table exists, a view (/BIC/M<Name of characteristic> of P or Q or P and Q is generated.

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Figure 2.21: Attribute Tables

Attribute for a master data-carrying characteristic.

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OBJVERS has two statuses: A = Active (the data can be used for reports) and M = modified/revised.CHANGED also has two statuses: I = Entry marked for insertion and D = Entry marked for deletion.

The following example throws light on the connection between OBJVERS and CHANGED:

Example:

Figure 2.22: OBJVER attribute

Step 1 shows the original data record for a master data-carrying characteristic. If changes are made to the master data, the system generates an additional data record (step 2), which has status M. You must activate this modified data record explicitly to make it

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available for queries. Up until activation, the active, unmodified data records are used in reports. After the master data has been activated, the modified data records are given status A and the old data records are deleted.

Figure 2.23: OBJVER attribute after Activating Master Data

Naming conventions in the attribute table:

/BIC/P<Name of characteristic> (for customer-defined characteristics that have time-independent attributes)/BIC/Q<Name of characteristic> (for customer-defined characteristics that have time-dependent attributes)/BI0/P<Name of characteristic> (for SAP standard characteristics that have time-independent attributes)/BI0/Q<Name of characteristic> (for SAP standard characteristics that have time-dependent attributes)

2.9.4. HierarchiesThe hierarchy table (H table) is used to store the hierarchical relationships between characteristic values, when external hierarchies are used for the characteristic. Only one H table is ever generated even if a characteristic contains several hierarchies. In other words, the H table contains all hierarchies.

If the complete hierarchy is time-dependent, the DATETO and DATEFROM fields do not appear in the H table. They appear as global fields (Meta information) in table RSHIEDIR. This also applies for the VERSION field for version-dependent hierarchies. Conversely, when the hierarchy structure is time-dependent, the date fields mentioned above appear in the H table.

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Figure 2.24: With Hierarchies

Figure 2.25: Hierarchy table

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Legend:HIEID - Internal hierarchy ID (unique ID) NODEID -Internal ID number of a hierarchy nodeIOBJNM - InfoObjectNODENAME - Name of the hierarchy nodeTLEVEL - Level of a hierarchy nodeLINK - Link indicator for a hierarchy nodePARENTID - Parent ID for a hierarchy nodeCHILDID - Child ID of a hierarchy nodeNEXTID - Next ID of a hierarchy nodeINTERVL - Indicator: Node is interval

Figure 2.26: Hierarchy Example

In this graphic, you can see the content of the H table after a hierarchy was loaded into SAP BW for characteristic 0COUNTRY, or after a hierarchy was created and activated (simplified display) in SAP BW. Setting the indicator in the INTERVL field permits intervals in this hierarchy, which means these are modeled in the J table. The second row of the example hierarchy is looked at more closely to help you better understand the structure of the table. You can see from the NODEID field that this is the second node of this hierarchy. The PARENTID field shows that the superordinate node has NODEID 1. In this example, the superordinate node is the root node. The CHILDID field denotes the subordinate node and the NEXTID denotes the adjacent (next) node. In this example, the subordinate node is Austria and the adjacent node is the USA

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2.9.5. SID TablesIn the below example, the connection between master data-carrying characteristics, navigation attributes, SID values and external hierarchies is looked at in more detail.

2.9.6. S TableThe S table is generated when a characteristic is activated. With one exception: When a characteristic is defined exclusively as an attribute. In other words, this characteristic can only be defined as the attribute of a master data-carrying characteristic in a different scenario. The graphic shows the structure of an S table. The key of this table is the characteristic for which the artificial key was generated. If the characteristic is compounded, the key is also made up of the compounded characteristic. The SID keys are automatically generated by the system when master data is uploaded.

The following graphic illustrates the relationship between the S tables and the tables belonging to the master data-carrying characteristic COSTC##. The diagram has been simplified to make it easier to understand.

Figure 2.27: S Table Example

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2.9.7. Table, Time Independent Navigation Attributes

The X table is only generated when at least one time-independent attribute is defined as navigation attribute. The key of the X table of the navigation attribute (naming convention S_<Name of attribute>) is the SID for the SID table belonging to the characteristic whose attribute is used here as the navigation attribute. The following graphic illustrates the structure of the table. We can also look at the subject matter involved here using the example of the profit center navigation attribute for the master data-carrying characteristic COSTC##. The graphic has been simplified.

Figure 2.28: X Table Example

2.9.8. Table, Time Dependent Navigation AttributesThe Y table is only generated when at least one time-dependent attribute is defined as navigation attribute. The key of the Y table of the navigation attribute (naming convention S_<Name of attribute>) is the SID for the SID table belonging to the characteristic whose attribute is used here as the navigation attribute. The following graphic illustrates the structure of the table. We can also look at the subject matter involved here using the example of the profit center navigation attribute for the master data-carrying characteristic COSTC##. The graphic has been simplified.

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Figure 2.29: Y Table Example

2.9.9. Changes to Characteristic InfoObjectYou can make the following changes to a characteristic after master data has been loaded: Display attribute (time-independent) Navigation attribute (time-independent)Display attribute (time-independent) Navigation attribute (time-dependent)Display attribute (time-independent) Display attribute (time-dependent)Display attribute (time-dependent) Navigation attribute (time-dependent)

The illustrated steps are displayed graphically in the Figure below.

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Figure 2.30: Changes to Attribute Tables

You can enhance the structure of master data-carrying characteristics after loading master data. You must bear in mind that you cannot delete fields of a structure containing data unless you have already deleted this existing data. In other words, if you want to remove the time-dependency of a display attribute, you must first delete the content of the table for the characteristic.

SID Table, External HierarchiesProviding that the ‘With hierarchies’ indicator was set in characteristic maintenance, the following SID tables are always generated with the H table.

SID Table from NodesIn this table, negative SID values are assigned to the nodes. The following graphic shows a K table for a characteristic with a time-independent hierarchy.

Inclusion TableIn theory, this table contains the same information as the H table, meaning that it displays the relationships between nodes/nodes and nodes/leaves. Here, the leaves (characteristic values) are assigned positive SID values and the nodes are assigned negative SID values (K table). The following graphic shows the I table for a characteristic with a time-independent hierarchy.

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Figure 2.30: Structure of K and I Tables

Legend:SID - SID of node within the hierarchyOSID - SID of node, original valueLINKNO - Link numberSVER - Version in key of inclusion tablePRED - Master data ID (predecessor)SUCC - Master data ID (successor)LISTNO - Sequence of inclusion relationshipsFACTOR - Factor with which the inclusion relationship enters the nodesNTYPEID - Internal ID for the node type

In this graphic, you can see example K and I tables after a hierarchy was loaded into SAP BW for characteristic OCOUNTRY, or after a hierarchy was created and activated (simplified display) in SAP BW.

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Figure 2.31: Hierarchy Example

InfoCube TablesThis section looks at the structure of the dimension tables and the F- and E tables.Dimension TablesWhen defining an InfoCube, characteristic InfoObjects are selected to be components of this InfoCube. They are then assigned to your user-defined dimensions. After the InfoCube is activated, the dimension tables are generated.

The columns of a dimension table do not consist of characteristic InfoObjects but of SIDs belonging to the characteristics. The characteristics were selected in the InfoCube definition and assigned to a dimension. DIM-ID consists of a unique INT4 key, as does the SID ID. When loading transaction data into the BasisCube, the DIM ID values are allocated uniquely, whereby each DIM ID value is uniquely assigned to a combination of SID values for the different characteristics. As you can see from the Figure 49 below the structure of a dimension table consists of a DIM ID column and of up to 248 SID columns.

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Figure 2.32: Dimension table after loading Transaction Data

Legend:[…] Technical name of InfoCubes# Numeration of the dimensions automatically allocated by the system. The DIM numbers contain the following elements: P, T, V, 1, 2... 9, A, B, C, D.P Data packageT TimeU UnitA 10B 11C 12D 13

2.9.10. Fact TablesEach BasisCube generates two fact tables, the F and E tables, after activation. Both tables have the same columns.

The structure of the fact tables in the SAP BW star schema is the same as that in the Basis star schema. The keys of the dimension tables (DIM IDs) are the foreign keys of the fact table. Each row of the fact table is uniquely identified by a combination of DIMID values.

2.9.10.1. Differences between the F and E tables:

The F table is optimized for data loading, since the data is always automatically partitioned using the package dimension. As a result, you are able to administer each individual data request separately.

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The E table is optimized for data requests, since the DMID of the package dimension is set to zero, thus reducing the key combination. Data records having the same key values are compressed. The figure 50 shows the relationship between fact tables and dimension tables.

Figure 2.33: F table Example

Naming conventions in the fact table:

/BIC/F<technical name of BasisCube> (F table for a customer-defined BasisCube)/BIC/E<technical name of BasisCube> (E table for a customer-defined BasisCube)/BI0/F<technical name of BasisCube> (F table for a SAP standard BasisCube)/BI0/E<technical name of BasisCube> (E table for an SAP standard BasisCube)

Transaction LISTSCHEMA shows you tables for the structure of the InfoCube. In addition, you can also display the attribute tables for the characteristics involved in the InfoCube. Hierarchy tables, text tables and the E table are not shown.

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3 Data Transfer Process in SAP BI

3.1. Overview of Data Transfer Process

SAP Netweaver 2004s includes a new DataSource concept, changes in InfoPackages, a new data agent called the data transfer process (DTP), the removal of the InfoSource as a mandatory data staging layer, and the consolidation of all data transformations into a single object called BI transformations.

3.1.1. Definition

DTP is an object that determines how data is transferred between two persistent objects – E.g. from Staging (PSA) layer to Enterprise Data Warehousing Layer, or from Enterprise Data Warehousing Layer to Architected Data Marts Layer.

3.1.2. Data flow in SAP Netweaver 2004s BI

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Figure 3.1: Data flow in SAP Netweaver 2004s BI

The figure 1.1 illustrates an example of a data update from the DataSource to an InfoProvider. The data can be updated from an InfoProvider to another InfoProvider using a data transfer process. The data transfer process can also be used to control data distribution from a BI system into any target outside of the BI system. For this purpose, a data transfer process with an open hub destination is used as the target. The following are the ways of data transfer:

The InfoPackage controls the transfer of data from the source to the entry layer of BI.

The data transfer process controls the distribution of data within BI.

By using Infospoke BI can be used as the source system, whereby he data can be loaded from BI to any other destination.

3.1.3. Key Benefits of DTP

Loading data from one layer to others except Infosources Separation of delta mechanism for different data targets Enhanced filtering in dataflow Improved transparency of staging processes across data

warehouse layers (PSA, DWH layer, ODS layer, Architected Data Marts)

Improves performance: optimized parallelization Enhanced error handling for DataStore object (error stack) Repair mode based on temporary data storage

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3.2. Data Transfer Process – Example

Within SAP Netweaver 2004s infopackages can only load data from source system to PSA without any semantic transformation. What can be done here is a technical transformation (e.g. conversion exit to transform data from external format to internal format). Transformations can be defined between a source and a target for data transformation or conversion. DTP is responsible for data loading from one persistent layer to the other. Every path from persistent source to target is a DTP. This means that besides InfoSource any other objects like InfoProviders, DataSources, DSO can be the source or target for the DTP. Consider the following example:

Figure 3.2: 2004s BI - Enhanced Data Flow Concept

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Infopackages only can load data from Source System to PSA without any semantic transformation

PSA will physically store the data Data can be loaded from PSA to DSO via DTP All the infopackages and DTPs should be included in process

chain for automations.

3.3. Creating and Managing DTP

3.3.1. Creating a DTP

Figure 3.3.1: Creation of Data Transfer Process

Go to RSA1 transaction (Data Warehousing Workbench) DTP is assigned to the target object Define transformation for the target object , by right clicking

on the target object and selecting ‘create transformation’ option(Add Transformation Slide)

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Figure 3.3.1.1: Creation of Transformation

Once transformation is defined, DTP can be defined for the target object by right clicking on the transformation.

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3.3.2. Tabs and Settings in DTP – Extraction Tab

Figure 3.3.2: Extraction tab inside DTP

Two types of extraction mode – Full and Delta For delta loading, we need to define two DTPs – one full and

one delta – to load data from source to target The filter function makes it possible to load a set of data to

the data target instead of the complete volume of data

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Different data selections can be made via different DTPs for the same or for different data targets

We can define the package size, whether the currency conversion should be switched on or whether it is possible to load the data from the change log of the DSO

3.3.3. Tabs and Settings in DTP – Update Tab

Figure 3.3.3: Update tab inside DTP

In update tab we can decide the type of error handling. There are 3 types:

‘No Update, No Reporting’ – Once errors occur, the whole data package is terminated. The request is not released for reporting

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‘Valid Records Update, No Reporting (Request Red)’ – Valid records are only updated but data is available for reporting only after manual processing of the request

‘Valid Records Update, Reporting Possible (Request Green)’ – Valid records are updated and also available for reporting

3.3.4. Tabs and Settings in DTP – Execute Tab

Figure 3.3.4: Execute tab inside DTP

Within the execute tab we can see all the process steps during the data loading

Process step filters out records with the same key

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It means if error handling is switched on and there are infoobjects which have the update mode ‘overwrite’ in the transformation, new records with the same key at the incorrect records will be filtered out during data loading

3.4. Error Handling of DTP

3.4.1. Error Handling Overview

The following flowchart illustrates how error handling works with the DTP. We have the option in the Update tab of DTP where we can choose whether error handling feature should be switched on or not.

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Figure 3.4: Flowchart for error handling

If we choose option 2 or 3 in error handling it will work as follows: Data is loaded via infopackage from source system to PSA

table. There is no error handling available for infopackage. In case of invalid records data needs to be reloaded from the source system.

Data from PSA to data target can be loaded via DTP. As error handling feature is switched on, the invalid records will be updated into the error stack. The correct records will be updated into the data target. After correcting the records in the error stack, these corrected data records can be loaded to the data target via ‘Error DTP’.

Error DTP is a special DTP which is responsible or loading data from the error stack to the data target.

3.4.2. Error Handling Overview

Possibility to choose in the scheduler to Abort process when errors occur Process the correct records but do not allow reporting on

them Process the correct records and allow reporting on them

Invalid records can be written into an error stack

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In DSO we have ‘overwrite’ as an update mode and hence sequence of the data is very important. Hence, keys should be defined for error stack to enable the error handling of DSO

Temporary data storage can be switched on/off for each sub step of the loading process

Invalid records can be updated into data targets after their correction

3.5. Error Stack in DTP

The following are some features of Error Stack: Stores erroneous records Keeps the right sequence of records – for consistent

DataStore handling Key of error stack defines which data should be detained from

the update after the erroneous data record After correction, Error DTP updates data from error stack to

data target Once the request in the source object is deleted, the related

data records in error stack are automatically deleted

3.5.1. Key of Error Stack

The key of the error stack should be as detailed as possible. If less fields are defined as key of the error stack, more records will be updated into the error stack. For example, if we select company code as error stack key and one record of a particular company is wrong, all records belonging to this company code will be written to

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the error stack. Thus, a detailed key leads to a small amount of entries in the error stack. The key of the DSO is defined as the initial key of the error stack by default. We can select all of them or some of them as the key for error stack.

Figure 3.5.1: Key of Error Stack

Key of the error stack can be defined in the Semantic Groups option

Maximum 16 key fields are possible It defines which data should be detained from the update

after the erroneous data record (for DSO) By default the key is same as complete target key (key of

DSO)

3.5.2. Error Stack Example – One Request

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Figure 3.5.2: Error Stack Example

The Order Number field is the key for the error stack. During the transformation, data record 02 of request 109882 is marked as containing errors. In addition to the erroneous data record, all subsequent data records for the request that contain the same key are written to the error stack. In this example, this is data record 03. This ensures that when error records are updated with the error DTP, the records are serialized correctly and newer data is not inadvertently overwritten by older data.

Figure 3.5.3: Error Stack Example

During the transformation, the data records for request 109882 are aggregated to one data record. If, for example, there is no SID for the

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characteristic value order number 1000, the record is interpreted as erroneous. It is not updated to the target. Those data records that form the aggregated data record are written to the error stack.

3.5.3. Error Stack Example – Multiple Requests

Figure 3.5.4: Error Stack Example

The Order Number field is the key for the error stack. During the transformation, data record 02 of request 109882 is marked as containing errors. In addition to the erroneous data record, all subsequent data records, including the following request that have the same key are written to the error stack. In this example, data record 01 for request 109883 is written to the error stack in addition to data record 02 for request 109882.

Figure 3.5.5: Error Stack Example

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The Order Number field is the key for the error stack. During the transformation, data record 01 of request 109883 is identified as containing errors. It is written to the error stack. Any data records from the previous request that have the same key were updated successfully to the target.

3.6. Temporary Storage for DTP

3.6.1. Settings and options

Settings for temporary data storage: Level of Detail

Tracing the erroneous records Tracing transformation by package Tracing transformation by record

Deletion of temporary storage With request status ‘green’ If request is deleted After X days

Figure 3.6.1: Temporary Storage for DTP

We can access the settings under the Goto menu.

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It provides help for tracing the erroneous records and transformations. Data records from different steps within the DTP can be stored temporarily. Stores complete set of data (erroneous as well as valid records) – unlike the error stack. The scenario recommended for using temporary data storage:

If the debugging mode is switched on Trace the erroneous records Trace transformation

We can trace incorrect data, incorrect transformations by package or by record. We can also define when this temporary data storage should be deleted. Also, we can decide for which loading step we wish to define the temporary data storage.

3.6.2. Temporary Storage and Error Stack

Figure 3.6.2: Temporary Storage & Error Stack

In the temporary data storage we can see all records – correct and incorrect. Incorrect records are marked with a special symbol.

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In the error stack we can see only incorrect records. Here we can correct these records manually.

3.7. DTP Monitor

3.7.1. Monitor Screen of DTP

Figure 3.7.1: Monitor Tab of DTP

This is integrated in InfoProvider management screen and integrated in DTP maintenance

Additional information: duration of each step Temporary storage access – if activated Error stack is displayed in DTP Monitor

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3.7.2. Handling Error with DTP

Following are the steps to handle data records with error with DTP:

1) Failed status of DTP in DTP Process Monitor because of invalid character in records. By clicking on Error Stack we can check error records.

2) Total of 3 records with error in source data.

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3) Correcting erroneous records in Error Stack by clicking edit button on top left.

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4) Creating Error DTP from the update tab of standard DTP.

5) Once Error DTP gets created, we can check the status of Standard DTP which is changed from create to display, and can also check the Error DTP under the Object for which we created the standard DTP.

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6) Error DTP

7) Schedule the Error DTP from Execute tab.

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8) In the Error DTP process monitor it’s showing 3 records that we corrected in Error Stack in earlier steps.

9) We can also check the status of Standard DTP, it’s also Green now (without errors).

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10) We can also check the records updated status of Standard and Error DTP in the manage tab of data target.

3.8. Managing InfoCubes-Data MaintenanceYou can use the Manage function to display the content of the fact table or concrete characteristic values (from a view of the table provided by the data browser). You can also repair and reconstruct indexes, delete erroneously loaded requests, roll up requests in the aggregates, compress the content of the fact tab1e, and reload requests that were deleted from the BasicCube. Select the BasicCube to be managed and from the context menu, choose Manage. Six tab pages appear:

Contents Performance Requests Rollup Collapse Reconstruct

The graphic displays the initial screen for InfoCube Management, including the tab pages mentioned above.

3.8.1. Maintaining InfoCube Data

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As shown in the Figure 4.22, from the Data Warehousing Workbench, right click the concerned InfoCube, and then select Manage.

Figure 3.22: Manage InfoCube

3.8.2. ContentsThis tab page lists all characteristics involved in the BasicCube for the associated dimensions. Via InfoCube Content, you can display the key figure values for the BasicCube, as well as the characteristics, SIDs for the characteristics and key figures of the Cube via a view. Fact Table can be used to display a list of all dimension keys and key figures for the individual transaction data records (the fact table content).

Via Selection, you can use a pre-selection to delete the data records matching these selection criteria from the BasicCube. If you select the cost center having cost center number T900000004250, all data records with this value are deleted from the BasicCube.

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Figure 3.23: Manage InfoCube: Contents

3.8.2.1. Display InfoCube Contents

Choose Contents tab, then click InfoCube content button, the following screen is displayed

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Figure 3.24: Display InfoCube Contents

In screen shown above, we specify conditions regarding what contents to be displayed. Some of the options are:

Choose Do not use any conversion to display the data in the database formats

Choose Use mat. Aggregates to display the data from an aggregate instead of the fact table if an appropriate aggregate exists

Choose Use DB aggregation to allow aggregation on the fields that are not the selection condition

Choose Output number of hits to add a new column in the display to show how many records in the fact table are used to produce each display row

Choose Display modified structures to display the M version master data. You use this option to check how the result would look in BEx should the characteristic data be activated

3.8.2.2. Delete InfoCube Contents Choose Contents tab, and then click Selective deletion button, the following screen is displayed

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Figure 3.25: Delete InfoCube Contents

In this pop-up window, we can specify the data to be deleted and how to delete them by clicking Delete selection button.

Figure 3.26: Delete Selections

In this window, under Options block we can do the following: Select Parall. Deg. during reconstruc to enter the number of

parallel processes to be used in reconstructing the table Select Switch off logging drng recons to improve performance

without logging the changes Select Display generated report to display the ABAP program

used to delete the data

3.8.3. PerformanceThis tab page allows you to influence load and query performance using the Delete Indexes, Repair Indexes and Create Index (Batch) functions.

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Figure 3.27: Manage InfoCube: Performance

Note that the status light should always be green. If no index/statistics data exist, the status lights will be red.

Delete Indexes (Immediately) to delete indexes. Now the status light turns red

Repair Indexes (Immediately) to create the indexes

Depending on the size of the InfoCube, it may take some time for the status light to turn green/redTo improve data loading performance, it is recommended that you delete the indexes, load the data, and the recreate the indexes. To automate this job, click Create Index button

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Figure 3.28: Delete Indexes

Check all the options and click Execute Changes button. Pl note that the next time when you load data into this InfoCube, you will receive a message, just click Yes button

Rolling up aggregates will automatically repair the aggregate indexes

In the same way, we can check, delete, and create statistics. If the DB Statistics status is red, click Refresh statistics To automate this process, click Create Statistics

Indexes are use to locate needed records in a database table quickly. SAP-BW uses two types of indexes B-tree for database tables and bitmap indexes for fact tables and aggregate tables. For a SQL statement, many execution plans are possible. The database optimizer generates the most efficient execution plan based on either the heuristic ranking of available execution plans. The cost based optimizer uses statistics to calculate the cost of available execution plans and select the most appropriate one for execution.

3.8.4. RequestsAll requests (data requests) that were loaded into the BasicCube are displayed on this tab page. In BW, each data load from BW Scheduler is considered as a request and is assigned a unique request number consisting of 30 characters and is stored as an integer value called a request id, in the data packet dimension of the InfoCube.

You can also delete request where required. The system displays whether requests have been scheduled for aggregation or already

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aggregated. You can also see whether requests have been compressed or have been scheduled for deletion.

You can enter an update period in the Request Display row to restrict the number of displayed requests.

On the Request tab page, you can see the status (red, yellow, green) of previous data load processes. The following table shows the values of the request ID status:

Figure 3.29: Manage InfoCube: Requests

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Table 3.8: Request Id QM Status

Each request has its own unique number (request ID). You can see this in the following graphic. By using a request ID (a unique key generated by the system) to indicate each request, the system can maintain a chronological update history. It allows the system administrator to identify specific upload sequences that had errors.

During extraction, the data requested in each request is taken from the source system and packed in packages within the request, before being loaded into SAP BW.

When executing a query, data packages with the status "red" or "yellow" cannot be taken into consideration. Data packages having status "green" that are loaded at a later time are also not used in the query here. If this were not the case, the consistency of data within the query could not be guaranteed.

To delete a request from the InfoCube, click Delete button. If the request has been rolled up into an aggregate or compressed, then you cannot delete it. If it has been rolled up, then the aggregate must be deactivated first. If it has been compressed, then all data in the fact table must be deleted first.

BW provides a useful function that allows us to check whether one data load request overlaps with another. For that select request 31501 and then click

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Figure 3.30: Manage InfoCube: Check Requests

A new session window opens and displays the request’s 30 character request number

Figure 3.31: Manage InfoCube: Check Requests Consistency

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Click to check the overlapping. The result contains information about the overlapping. If overlapping is present, the result also tells us whether we can delete the request.

3.8.5. RollupIf activated and filled aggregates exist for the BasicCube and you then load new requests into the BasicCube, you need to roll these up into the aggregates as well.

Figure 3.26: Manage InfoCube: Rollup

3.8.6. Compress/CollapseAs mentioned above, each data load process is uniquely identified within a BasicCube using a request ID, which is included in the package dimension. This allows you to look at individual requests in detail. Using request Ids can have the effect that a data record with the same content (where all characters are the same except for the request ID) appears more than once in the fact table. The result is an unnecessary increase in the data volume. The greater data volume reduces performance in Reporting, since every time a query is executed; the system accesses data via the request ID. This is because data records are only aggregated within a request. To save storage, space and improve read performance, you can compress a

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BasicCube, whereby the request ID is set to null. Data records with the same dimension key are aggregated. During compression, data records are written to the BasicCube E table and the compressed requests are removed from the F table. Newly requested requests are written again to the F table and can then be compressed if required (see graphic).

Figure 3.27: Compressing the InfoCube

This function comes with a disadvantage: Compressed data can no longer be deleted from the InfoCube using request IDs. In other words, BasicCube data can either be deleted via Selective Deletion or it can be deleted completely.

For performance reasons, and to conserve storage space, we recommend that you compress the BasicCube as soon as you know that the request was loaded correctly and that no more data is to be deleted from the InfoCube.

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Figure 3.28: Manage InfoCube: CollapseThe Collapse tab page deals with the InfoCube compression. As mentioned earlier, each InfoCube has two fact tables: the F and E fact table. We load data into the F fact table, where the dates are grouped according to load request. The F table allows us to check for overlapping requests and to delete unnecessary requests. Note that F fact table is an overhead in terms of performance and space utilization. Further, while executing a query, the OLAP processor must aggregate key figures to eliminate the request information in the data packet dimension.

Therefore, BW allows us to aggregate the F table and saves the aggregated data in the E fact table and this process is called InfoCube Compression. Upon compression, request id is set to zero and hence not available.

For instance, we want to compress request 31839, enter 31839 into the Request ID and then click . BW will compress 31839and request below 31839. However, to delete records whose key figures are all 0, select the With Zero Elimination.

On order to delete a compressed request, we must either delete all off the E Fact table data or use the Request reverse posting (Read

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everything in manually) function in the Monitor-Administrator Workbench.

3.8.7. Automating rollup and InfoCube compression:You can also automate the rollup and compression of the InfoCube for newly loaded data records. You can do this by calling up, from the context menu for the InfoCube to be managed, Manage Environment Automatic Request Processing. You can set the following indicators here:

Set quality status to OK Roll up data in the aggregate Compress after rollup

Figure 3.29: Manage InfoCube: Set Quality Status

3.8.8. ReconstructYou can use this function to reconstruct requests that were already rolled up into a BasicCube and that have since been deleted (update requests into the BasicCube).

This function can only be used when the data is held in the PSA.

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By accessing the Contents tab page in BasicCube management, you are able to extract BasicCube data into an external file, or a new or existing DB table. This is useful in situations where some of the collected data is to be used in other analysis tools (for example, a different planning tool than SAP Strategic Enterprise management). You must make the following settings on the selection screen:

Select the fields for output in the fileSpecify selection values for characteristicsSelect the file type and name of the file to be generated, as well as the location where the file is to be saved.

The system transfers the data after you confirm your entries. By default, the data is returned as a display list.

Figure 3.30: Manage InfoCube: Reconstruct

3.9. Using BW Monitor

BW Monitor enables us to trouble shoot during the load process. Simply put, you may use BW Monitor to display the status of data loads and find out when, where, and how errors (if any) occurred.

Select the InfoCube, and then click .

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Figure 3.31: Monitor Button

Click to continue. Leave Date Selection blank, as we want to list the status of all data loads.

Figure 3.32: Date Selection

We see the status of all data load (successful and failed). Double click on the last failed load operation to get the details.

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Figure 3.33: Monitor: Status

Click under Status tab to display the error. The message box is displayed.

Figure 3.34:Error Messages

Under the Details tab page, we can see how the data flowed and where the errors have occurred.

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Figure 3.35: Monitor: Details

To review the status of other data loads, we can click New Selection (F5) button .

Figure 3.36: Monitor: New Selection

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Figure 3.37: Monitor: Selection Data Request

In the above screen, we can specify selection conditions to display the status of the data loads.

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4 Data Store Objects (DSO)The ODS object played an important role in the former version of BI warehouse management. This has been succeeded by the compatible but superior object type “Data Store Object” in SAP NW 2004s.Data Store Object offers certain performance improvements as well as enhanced capabilities in analysis. Enhanced capabilities at one glance:

Full compatibility to the former ODS Object – No migration needed

DSOs can be used in analysis – Regardless of settings and type

New Data Store Object Type – Write – optimized Transactional ODS is now called as ‘Data Store Object for

Direct Update’.

Various Types of the Data Store Objects1. Standard2. Direct Update 3. Write-Optimized

4.1. Data Store Object definition:

1. Context Menu: Direct Access to display data Additional Functions

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Figure 5.1 Additional functions of DSO

2. New Data Store Object Settings:

Data Store Object Type: Can only be set/changed if there is no data in the DSO.

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Figure 5.2: New DataStore Object Settings

SID Generation upon Activation – Replaces “BEx Reporting” and is pure performance setting. Reporting is possible if this is not set.

Other settings are similar to those available in 3.X ODS.

4.2. Data Store Object Types

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4.2.1. Data Store Object Types Overview:

Data Store Object Type

Primary Usage Table Structure Integration into DataflowEDW

Layer

ODS Layer

Delta Capability

Fast Access(No Activation)

Others Activation Queue

Active Data

Change Log

Standard X X Delta determination from after images on record level

X X X Via Staging(DTP)

Write- Optimized

X On request level

X Staging Layer, especially for large sets of data with unique key

X Via Staging(DTP)

Direct Update

No delta capability

X For external applications and analysis processes(APD)

X Via APIs, staging into subsequent targets possible

4.2.2. Standard Data Store Object:

Figure 5.2.2: Standard DataStore Object

1) SIDs Generation upon Activation

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Improves Query performance Queries are also possible if SID values are not

generated

2) Unique Data Records Available only if ‘SIDs Generation upon Activation’ is

set. Activation Process is optimized.

3) For non-reporting scenarios write – optimized DSOs are recommended than standard DSOs

4) Enhanced Activation Process: Instead of the key field request GUID there is a key

field request SID used within the Activation Queue Because of this modified structure there is no

“expensive” join to the request SID table necessary. Also there is the package fetched used instead of the

single dataset fetch during the activation process (In addition to that there is only one loop over the activation loop implemented now; for restarting there is no further loop necessary because the packages are stored temporarily in the cluster tables)

5) Structure (Tables): Structure of the Standard Data Store Object is similar to that of the standard ODS in BW3.5 Contains -

1. Activation Queue2. Active Data 3. Change Log

Activation Queue:

Used to store the data to be updated in the Data Store Object which has not been activated.

After activation data is deleted from this table Technical Key: Request SID, Package ID, Record

Number

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Figure 5.2.2: Technical Keys Of Activation Queue

Active Data Table:

Structure same as the Data Store Object definition. Also called as ‘A-Table’.

Technical Key – Key fields defined in the DSO When the request is activated data moves from

Activation Queue to this table.Change Log:

Change history for delta mechanism from the Data Store Object into other infoprovider

Key Fields – Request GUID, Package ID, Record Number.

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Figure 5.2.2: Structure of DSO

Standard DataStore Object - Activation Performance Improvements of the activation process:

Figure 5.2.2: Performance Improvements of the activation process

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The Activation Process features the following:

Single scan on the Activation Queue for all parallel activation processes

Packages are stored in cluster – No scan necessary at the restart

Activation Queue contains Request SID (instead of GUID) – no join with request SID necessary

Package fetch instead of single select

4.2.3. Write-optimized Data Store Object:

Figure 5.2.3: Settings Of Write –optimized DSO

1. Definition:

The Data is stored simply in one version Only one table exists – Active Data Table with key and data

fields of its definition Active Data Table is partitioned according to the Request ID. There is no change log table - delta capabilities are not

neededo To access most recent data use a date field in the Data

Store Object definition There is no SID generation during the data load- BEx-

Reporting is switched off.

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It can be used for transformation upload scenarios. Also it is possible to extract data.

There is direct reporting possible on this object without activation – Also Infoset can be used to join the Active Tables

Also it is possible to include this object into multiprovider

2. The uniqueness of the data can be switched off with a check box

Definition:- This indicator is only relevant for write-optimized Data Store

Objects. The technical key for these objects in the active table always consists of the fields Request ID, Data Package and Data Record. The infoobjects that appear in the maintenance dialog in the folder Key Fields from the semantic key of the Data Store Object.

- If this indicator is set, a unique index with the technical name “KEY” is generated for the infoobjects in the semantic key.

- If this indicator is not set, the active table of the Data Store Object could contain several records with the same key.

3. On Data Warehousing Workbench:

4.2.4. Data Store Object for the Direct Update:

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This icon indicates that this is Write-Optimized DSO

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Figure 5.2.4: Settings Of DSO for Direct Update

1. Definition:

- The Data is stored simply in one version- Only one table exists – Active Data Table with key and data

fields of its definition- This type of the Data Store Object can be used for analysis

processes e.g. with the Analysis Process Designer (APD)- It can not be used for transformation upload scenarios – there

is no loading into Data Store Object for direct update within BI. But it is possible to extract data.

- There is no direct reporting on this object possible yet – instead you may use an infoset to join the active tables.

- Not possible to include the object into multiprovider.- The Data Store Object for direct update can be used for

transactional data.

2. The Data Store Object for direct update is perfect for using it for external data. There is an API available with various function modules:

- BAPI BAPI_ODSO_READ _DATA_UC- RSDRI_ODSO_INSERT- RSDRI_ODSO_INSERT_RFC- RSDRI_ODSO_MODIFY- RSDRI_ODSO_MODIFY_RFC

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- RSDRI_ODSO_UPDATE- RSDRI_ODSO_UPDATE_RFC- RSDRI_ODSO_DELETE_RFC

3. On Data Warehousing Workbench:

4.3. Data Store Object Administration

4.3.1. Overview

Figure 5.3: New Monitor Concept in DSO

There is new monitor concept installed for the Data Store Object administration: Load monitor like 3.X Monitor Logs for DSO- request processing

Frames like ‘Contents’ and ‘Reconstruction’ are same as that of earlier version.

a) Load Monitor:

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This icon indicates that this is DSO for Direct Update

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Monitor view is divided into two frames Header view and Details view

Header View: Displays all relevant objects which do depend to the transfer process.

Figure 5.3: Header View

Details View: Displays all the relevant steps with timestamp of the transfer process.

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Figure 5.3: Details View

b) Logs for DSO – Request Processing:

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Figure 5.3: Logs for DSO

1. This log information can also be viewed via transaction RSODSO_SHOWLOG

Parameters Required: Request ID Name of the Data Store Object

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Figure 5.3: Transaction RSODSO_SHOWLOG

2. Different entry points are possible via transaction: Activation of Data Loading Data Delete Data Rollback of Data All operations

3. All operations are also displayed when clicking on the icon within the DSO administration Manage View.4. For each operation there is detailed information.

4.4. DataStore Object Administration - Performance:

Following are some administration points to be noted for optimum performance

1. SID Generation:

Do not mark the check box when there is no reporting Time consuming characteristic SID generation is avoided

within activation.

1. Partitioning/Clustering

Database maintenance features for having better read-write and delete access.

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Write-optimized DSO is automatically partitioned. Manual Partitioning according to OSS notes 565725 and

742243

3. Indexing:

If reporting selection criteria do not match the key specifications secondary indices help to improve query response time.

Index maintenance can be done within the Data Store Object definition.

4. Data Modeling Tips:

Only as many key fields as necessary Reduce granularity as far as possible Only as many data fields as necessary Reduce information fields as far as possible Load only as many data records as necessary

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5 MultiProvidersSometimes, there are complex reporting demands for which you need to combine data from several InfoCubes. These complex requests are carried out using a MultiProvider. MultiProviders enable us to combine any InfoProviders you choose in order to build a new semantic layer for reporting, with having to change the data store.

An InfoProvider is an object using which queries can be defined and evaluated. InfoProviders are the objects / views relevant to reporting. For this reason it does not matter if these objects contain data or not. InfoProviders can be:

InfoCubes (BasisCubes, virtual cubes) ODS objects InfoSets MultiProviders

According to the above definition, data targets are also always InfoProviders (but not vice versa).

A MultiProvider is a special InfoProvider that combines data from several InfoProviders, providing it for reporting. The MultiProvider itself does not contain new data. Its data comes exclusively from the InfoProviders on which it is based. A MultiProvider can be made up of various combinations of the following InfoProviders:

InfoCube ODS object InfoObject InfoSet

A MultiProvider allows reporting using several InfoProviders. For example, InfoCube and InfoCube: You have an InfoProvider with actual data for a logically self-contained business area as well as a corresponding InfoProvider with plan data. You can combine t6he two InfoProviders ZINTO A MultiProvider to compare actual and plan data in a query. a combination of two InfoCubes was still referred to as a MultiCube in BW Release 2.0b / 2.1 c.

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Figure 6.1: MultiProvider Concept

5.1. Advantages of MultiProvider This concept provides you with advanced analysis options,

without you having to fill new and extremely large InfoCubes with data. You can construct simpler BasisCubes with smaller tables and with less redundancy.

The individual BasisCubes and ODS objects can be individually partitioned.

MultiCube only exists as long as a logical definition. The data is still stored in the InfoProviders on which they are based. In a MultiProvider, each characteristic of the MultiProvider must match precisely one characteristic or navigation attribute in each InfoProvider involved.

5.2. MultiProvider, Application ExampleThree BasisCubes are available. The first BasisCube contains customer order data, the second contains delivery data and the third billing data. The three BasisCubes have the following common characteristics: ONUM(order number), CUS (customer) and PROD (product).

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Figure 6.2: Basic Cubes

You can now define a MultiProvider that includes these common characteristics as well as the key figures of the BasisCubes involved. The MultiProvider can now be used in queries.

Figure 6.3: MultiProvider

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Sales Order Delivery Billing

OOAT : Order Date (C)SALP : Sales Person (C)OQTY : Order Quantity (K)OPRI : Order Price (K)

DDAT : Delivery Date (C)DELP : Delivery Person (C)DQTY : Delivered Quantity (K)DPRI : Delivery Price (K)

BDAT : Billing Date (C)BILP : Billing Person (C)BQTY : Billing Quantity (K)DPRI : Delivery Price (K)

ONUM : Order Number (C) ONUM : Order Number (C) ONUM : Order Number (C)CUS : Customer (C) CUS : Customer (C) CUS : Customer (C) PROD : Product (c) PROD : Product (c) PROD : Product (c)

Sales ProcessONUM : Order Number (C)CUS : Customer (C)PROD : Product (C)OQTY : Order Quantity (K)OPRI : Order Price (K)DQTY : Delivered Quantity (K)DPRI : Delivery Price (K)BQTY : Billing Quantity (K)BPRI : Billing Price (K)

Sales Order Delivery Billing

OOAT : Order Date (C)SALP : Sales Person (C)OQTY : Order Quantity (K)OPRI : Order Price (K)

DDAT : Delivery Date (C)DELP : Delivery Person (C)DQTY : Delivered Quantity (K)DPRI : Delivery Price (K)

BDAT : Billing Date (C)BILP : Billing Person (C)BQTY : Billing Quantity (K)DPRI : Delivery Price (K)

ONUM : Order Number (C) ONUM : Order Number (C) ONUM : Order Number (C)CUS : Customer (C) CUS : Customer (C) CUS : Customer (C)PROD: Product (C) PROD: Product (C) PROD: Product (C)

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A query executed using a MultiProvider is divided up across the involved InfoCubes using several select statements, which can be processed in parallel. This gives you further improvement in system performance. The OLAP processor presents the combination of the results from the individual select statements as the query result.

In case where a characteristic does not have a corresponding characteristic in a particular BasisCube, the data is presented in the query with the characteristic value Not Assigned.

Figure 6.4: MultiProvider Queries

A key figure contained in a MultiProvider must be selected from at least one of the InfoProviders involved. Generally, the key figure is supplied from precisely one InfoProvider. However, there are some situations in which it makes sense to select from more than one InfoProvider.

It is both desirable and sufficient for you to select from precisely one InfoProvider involved in cases where a key figure, for example 0SALES (sales) is stored redundantly in several InfoProviders (in other words, entirely contained in all value combinations of the characteristics). If this is not the case, the value appearing more than once in the MultiProvider would be incorrectly added. However, if 0SALES is saved, say, as an actual value in one InfoProvider and as a plan value in another, you must select from several

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MultiCube Sales Process

Info Cube Billing

Info Cube Delivery

Info Cube Sales Order

MultiProvider Queries

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InfoProviders. This avoids overlaps in the data records (where the revenue from several InfoProviders is distributed in disjointed form).

5.3. Creating a MultiProvider

1. In the context menu for your InfoArea, right Click and choose Create MultiProvider…

Figure 6.5: Create MultiProvider…

2. The following screen is displayed: Give the name of the MultiProvider, Short Description and InfoArea Name, and then click on

Figure 6.6: Edit MultiProvider

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In the subsequent window, you can select the objects involved in the MultiProvider viz., InfoCubes/ODS Objects…tab page and the click

Figure 6.7: Select Relevant InfoProviders

3. Use Drag&Drop to transfer the required InfoObjects into MultiProvider. Entire Dimension of cube can be transfer into multiprovider.

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Figure 6.8: Edit MultiProvider: Characteristics

4. You use Identify Characteristics and Select Key Figures to make InfoObject assignments between MultiProviders and InfoProviders.

Figure 6.9: Identification of Characteristics involved

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5. Check, save and activate, your MultiProvider.

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6 AggregatesMost end users need to access only a subset of information. In that case, we would create a new InfoCube, which contains only that information you are seeking. This new InfoCube is actually a subset of the original InfoCube. Because the new InfoCube is smaller, this requires disk I/O volume during execution will be smaller too, and thus see an improved query performance. SAP implements this idea in BW and calls the new InfoCube an aggregate. An InfoCube can have multiple aggregates, and the aggregates are transparent to users. It means that we create queries on InfoCubes, not on aggregates. For a query run or a navigation step, the BW OLAP processor is responsible for selecting an appropriate aggregate. If no appropriate aggregate exists, the BW OLAP processor will retrieve data from the original InfoCube.

An aggregate is a materialized, aggregated view of BasicCube data. In an aggregate, the dataset for a BasicCube is stored redundantly and persistently in summarized for on the database. Like database indexes, aggregates also improve system performance without the need for end-user intervention or end-users having to know how to perform this procedure,

Aggregates can be created for the following: Characteristics Attributes Hierarchies

6.1. Using Aggregates The large quantity of data records in the fact table leads to poor query response time. By using the aggregates, the data volume is reduced for each query access, because the data is stored in a compressed form. This increases the reading performance for queries. Within the aggregate, data can be summarized by time, by characteristics, or by the available hierarchies.

Too many aggregates may not be feasible because the rollup process takes time and in spite of the query performance getting improved the ETL process would take more time.

Aggregates should be created in the following cases:

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Executing and navigating query data lead to delays when using a group of queries

You want to expedite the execution and navigation of a specific query.

You frequently use attributes in queries. You want to expedite reporting using characteristic hierarchies in

which you aggregate specific hierarchy levels.

6.1.1. Screen Info for an AggregateAn aggregate is built of characteristics and navigation attributes from a BasicCube. Both time-dependent attributes and hierarchies can be used in aggregates. Compression takes place, using characteristics that are not used in the aggregate. When you create and activate an aggregate for a BasicCube, then fill it with data; the OLAP processor dynamically accesses this aggregate. When navigating the different results remain consistent. For the end user, the aggregate is transparent. New data is loaded for a defined time period using logical data packages (requests) in an aggregate. After this process, known as the roll-up, the new data is available for reporting. Only one aggregate can be used for each query step. A Basic-Cube can have more than one aggregate. If several aggregates are created for a BasicCube, these aggregates are all checked when executing a query from the OLAP processor. During this check, the OLAP processor reads all BasicCube aggregates and chooses the aggregate that is suitable for the query definition. The aggregate hierarchy is an exception. If the aggregate for a hierarchy node from the OLAP processor is not read, the OLAP processor likewise does not examine the rest of the hierarchy aggregates

Aggregates are defined in the following way-‘*’ – Inclusive; Compression is created using the characteristic‘ ’ – Exclusive; Compression is not created using the characteristic.‘F’ – Inclusive with a fixed value; Compression of characteristic with a defined, fixed value.‘H’ – Hierarchy level; Compression of characteristic for a defined hierarchy level.The following tables exemplify how this works –

Fact Table : Sales Data

Country Customer

Sales

Germany

Siemens 25

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Germany

ABB 20

USA P&G 10India ABB 30USA Colgate 20India Siemens 50

Aggregate Tables: Sales Data

Country: *Customer: Empty

Country Sales

Germany 45USA 30India 80

Country: EmptyCustomer: *

Customer SalesSiemens 75ABB 50P&G 10Colgate 20

Country: F, IndiaCustomer: *

Country

Customer

Sales

India ABB 30India Siemens 45

Country: H, Level 2Customer: Empty

Country SalesAmerica 30Europe 45Asia 80

Table 3.1: Aggregate Types

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6.1.2. Properties at AggregatesTechnical properties, such as content and status properties, belong to the properties of aggregates. This information is stored in the RSDDAGGRDIR table.Among other technical properties, the aggregate name that is generated by the system is included. This name is unique and consists of 25 characters (RSDDAGGRDIR table; AGGRUID field). For the database table, an aggregate name made up of 6 whole numbers is created that is specified in a special number range (from 100000).

Content and status properties can be indicated as follows. In order to use aggregates for reporting, they all have to be active and filled. If the use of one or more aggregates is prevented, three options are available:

Switch off the aggregate -The aggregate is still filled with data, but is not used by the OLAP processor.

Deactivate the aggregate -The aggregate data is deleted. However, the aggregate definition remains.

Delete the aggregate - The aggregate data and definition are deleted.

There is also the option of including several characteristics in an aggregate. Combinations in the restrictions, such as fixed values or hierarchy levels, are possible here. If the BasicCube uses a key figure, for which an exception aggregation was defined, this characteristic has to be included in the aggregate and defined as ‘*’. Restrictions are not permitted in this case (for example, fixed value 'F'). The combination of structurally time-dependent hierarchies and time-dependent characteristics is not possible.

6.1.3. Technical Construction of an AggregateAggregates are represented in the system as an aggregate cube. This means that each aggregate consists of two fact tables (E and F) and at least two Dimension tables (package and customer-defined dimensions; the unit dimension is not mandatory). The technical naming convention is the same as that for a BasicCube. Instead of the technical name of the BasicCube for the tables, the technical name for the aggregate for the database is used here (remember, it is generated from a number range from 100000). The technical construction of the aggregate differs in the following ways from that of a BasicCube.

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When up to fifteen characteristics are transferred into the aggregate, the SAP BW system creates no "real" dimension. In this case, a line item dimension is created. This refers to flat aggregates. The exception to this is the data package and time dimensions.

If more than fifteen characteristics are transferred into an aggregate, the SAP BW system proceeds in two different ways: If two or more characteristics come from one BasicCube

dimension, then the DIM ID for the BasicCube is entered as a key in the fact table.

If only one characteristic comes from one BasicCube dimension, then the SID is entered as a key in the fact table. Again, this concerns a line item dimension.

6.1.4. Aggregate SelectionThe selection of the aggregate to be created conforms to the queries that were defined for the respective BasicCube. However, the question should be asked here if the aggregates created are at all meaningful or useful for business. Note the following points before creating an aggregate:

The selection of characteristics for the aggregate needs to be restricted so that you can keep data quantity in the aggregate to the minimum. You can do this by having several data records occupy a similar characteristic specification (aggregated performance). On the other hand, you need to only select characteristics that are often used in the queries.

Only create aggregates if a specific demand exists (queries)Create a sample aggregate from the statistics if you are not sure

which characteristics you want to transfer into your aggregate. These statistics are based on data from the statistics cubes (technical content lesson)

If time-dependency (key date) is needed in your aggregate, this key date is filled by using a key date or a variable

6.1.5. Roll-Up of AggregatesIncluded in the roll-up is the loading of data into the aggregate. This occurs as the BasicCube requests are loaded into the aggregate. A roll-up can consist of one or more requests. The request ID controls the request in the roll-up. This request ID is stored in the package dimension of the BasicCube. A field in the RSDDAGGRDIR table, referred to as the ‘Read Pointer’, points to the latest request, which was rolled up in the aggregate. Once the request is rolled up in the aggregate, it

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becomes available for reporting. The roll-up process can be automated in the Manage Data Targets screen by following the menu, Environment Automatic Request Processing Roll up data in the Aggregate.

Figure 6.1: Request before Rolling Up

In the above figure, the first request with number 41239 was not rolled up into the aggregate and is also Request is available for reporting is also not clicked, hence is not available for reporting. In the RSDDAGGRDIR table, a read pointer is set to request 40424 in the RNSID_TO field. This read pointer refers to the OLAP processor, which request is available for reporting during the query execution.

After the roll-up of request 41239, you see that the reporting request is available, and the read pointer in the RSDDAGGRDIR table is set to request 41239.

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Figure 6.2: Request after Rolling UpSteps to follow for Roll-Up:

1. A new request is written into the BasisCube leads to a new RNSID in the fact table.

2. Roll-up the new request into the aggregate3. During the roll-up, the read pointer is set to the new request.

This new request is now available for reporting.

6.1.6. Compression of AggregatesYou can automatically compress aggregates during the roll-up. This causes the request(s) to be written into the E fact table of the aggregate cube during the roll-up. This removes the request ID. By doing so, a compression can be executed across all the requests. Data records with the same characteristic value are aggregated. If a request has to be deleted after the compression then all aggregates have to be deactivated first. This can take a long time. If you compress the aggregates first when the InfoCube is also compressed, then it is possible to delete a rolled-up but not yet compressed request without taking up a great amount of time.

6.1.6.1. Read Pointer A read pointer reads the position of a new SID for combinations of characteristics; for example, a new Request ID is generated during

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a change in an InfoCube and related aggregates (roll-up). Reporting uses only the request up to the RNSID of the Read pointer.

Read pointers are used to keep aggregate data and cube data in sync.

6.1.6.2. RNSID (Request Set ID) RNSIDs are package IDs or InfoPackage IDs. The RNSID represents the chronological update history defined with a unique key created from the system for each load request and with the request for each data record.

Benefits of the RNSID include:

Improved performance Identification of separate loads of data in the InfoCube and

aggregates The RNSID is useful when it is necessary to remove or reload

specific batches of data to/from the InfoCube and aggregates. Each data upload has a Request Set ID in the aggregates and

the InfoCube. The RNSID column is hidden in the fact table.

6.2. Aggregates and Master Data ChangesIf you change attributes or hierarchies from characteristics that were used in aggregates, then it is necessary to make appropriate structure changes in the aggregates. Because changes to these would invalidate the aggregates, you cannot activate hierarchies or navigational attributes directly. You can only mark them for activation. By doing so, two versions exist for navigation attributes and hierarchies - an active and a modified version. The change then occurs by means or a realignment run for hierarchies or attributes. While the changes are made and realignment run in active, reporting continues to use the old data until the aggregates are rebuilt.

Note the following with realignment runs:The (time) effort for a realignment run depends on the number of

navigation attributes (or hierarchies) and frequency of master data uploads for the respective characteristic InfoObject.

During the realignment run you are only able to report on the old non-cumulative from attributes/hierarchies. Active versions of the changes are available when the change run has finished. This also applies to reporting using InfoCubes that are not affected by the realignment run, but do use the modified hierarchies and attributes.

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You can check which objects are affected by the realignment run by using the monitor function for the realignment run. This shows you which characteristics and hierarchies are activated, and which aggregates and BasicCubes are affected. If the realignment run is active, then you can see whether the changes are already active for each aggregate.

If characteristic data have been changed, we must activate the change before BEx Analyzer can display the new data. To change the data entry, select the row and then click . Refer to figure:

Figure 6.3: Maintain Master Data

To change material HIBE to PAI and Short description to MONEY and then save the changes. Go to SE16 and type /BIC/PMATERIALC-the name of the database table. The following screen is displayed.

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Figure 6.4: Master Data Change

For material 59, you see that the A in the OBJVERS column indicates that the corresponding entry is active, and the M indicates that the corresponding entry is modified and to be activated. The D in the CHANGED column indicates that the corresponding entry is to be deleted, and the I indicates that the corresponding entry is new one.

Note: Upon execution of a query, you observe two things: A query always retrieves the current texts as the text table

does not maintain the history of changes A query always retrieves active master data i.e., HIBE instead

of PAI.

There are two ways of activating master data. Choose Modeling->InfoObject->Your InfoArea->Your Characteristics (MaterialC). Right click choose Activate master data, as shown in the figure.

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Figure 6.5: Activate Master Data

The second way Apply Hierarchy/Attribute Change not only allows us to activate master data but may also be applied for hierarchy changes. Further, if the attribute you changed happens to be an aggregate.

Steps to follow: Select Apply Hierarchy/Attribute Change… on the tools menu (either from InfoObjects or InfoProvider tree.

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Figure 6.6: Apply Hierarchy/Attribute Change

Figure 6.7: Execute Hierarchy/Attribute Changes: InfoObject List

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In the above screen, you can schedule the activation by clicking to execute in background mode or schedule

for immediate execution by selecting . To list changed characteristic choose . The next dialog box is displayed which shows list of changed characteristics.

Figure 6.8: Choose InfoObject from the List

You cannot delete master data if they are used by other BW objects. The SID table /BIC/SMATERIALC contents are shown in the next screen. The X in column DATAFL indicates that an InfoCube uses the corresponding entry, and the X in column INCFL indicates that a hierarchy uses the entry.

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Figure 6.9: DATAFL field from the S Table

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7 Admin Cockpit

Your organization works productively with BW. You want to get an overview of how the system is used, the volume of data and the resources consumed. You also need constant updates on how the system response time changes over time.

8 Process Chains

8.1. Overview of Process Chains

8.1.1. DefinitionA process chain is a sequence of processes that wait in the background for an event. Some of these processes trigger a separate event that can start other processes in turn.

8.1.2. UsesIn an operating BW system there are a multitude of processes in addition to the loading process that occur regularly.Process chains help us to

Automate the complex schedules in BW with the help of the event-controlled processing,

Visualize the schedule by using network applications, and Centrally control and monitor the processes.

8.1.3. Data Load Cycle

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Figure 8.1: Typical Data Load Cycle for Process Chain

8.1.4. Types of Process Chains

Local Chain: This is the simple process chain. Meta Chain: This is the main chain which contains one or

more local chains Remote Chain: This is the process chain which is in some

other system than in BW

8.2. Structure of Process Chains

A process chain consists of a start process, individual application processes and the so-called collection processes. The start of the process chain is defined with the start process. All other chain processes are scheduled to wait for an event. The application processes are the actual processes. BW supports process types of the following categories:

Load process and post processing processes Data target administration processes, Other BW processes ABAP Program

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We also have the option to include process chains as processes themselves in another process chain. In doing so, we need to determine whether we are dealing with a local process chain or a remote process chain. A local process chain comes from processes that are scheduled in the BW system itself. It is scheduled as a process in the same BW system. A remote process chain calls a process chain that needs to be run by using a destination in another system. After terminating the process chain in another system, this is confirmed in the BW system and terminates the remote process chain there.

We can access the process maintenance screen via transaction RSPC. It enables:

Easy creation of process chains via drag & drop Creation of items

Figure 8.2: Transaction RSPC – Process Chain Maintenance

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8.2.1. Collector Processes Collectors are used to manage multiple processes that feed

into the same subsequent process. The collectors available for BW are: AND: All of the processes that are direct

predecessors must send an event in order for subsequent processes to be executed.

OR: At least one predecessor process must send an event. The first predecessor process that sends an event triggers the subsequent process.

EXOR: Exclusive OR is similar to regular OR, but there is only ONE execution of the successor processes, even if several predecessor processes raise an event.

Collector processes allow the designer of a process chain to trigger a subsequent process based on whether certain conditions are met by multiple predecessor processes.

8.2.2. Application processes Application processes represent BW activities that are

typically performed as part of BW operations. Examples include:

Data Load HACR Aggregate Rollup Reporting Agent Settings

Other special types of application processes are: Start Variant – a process that exists to trigger process

chain execution (It is part of every process chain) ABAP program Another process chain Remote process chain Operating system command Customer built processes

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8.2.3. Start Variant

Figure 8.3: Start variant configuration

The start variant can be used by just one process chain Start variant helps in specifying the condition for the start of

the process chain

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9 Generic R/3 Data ExtractionIn this chapter we will see how to use generic R/3 data extraction capability. Generic R/3 data extraction allows us to extract virtually any R/3 data. In other words, Generic data extraction is a function in Business Content that supports the creation of DataSources based on DB tables, views or InfoSet queries. In this chapter we will discuss how to load the appropriate R/3 data into the new material characteristic ZMATERIAL. Its master data will be extracted from MARA.

Fields

Data Type

Length

Decimal Places

Short Text

MANDT

CLNT 3 0 Client

MATNR

CHAR 18 0 Material Number

MTART

CHAR 4 0 Material Type

MATKL

CHAR 9 0 Material Group

Table 9.1: MARA fields for ZMATERIAL Master Data

Fields

Data Type

Length

Decimal Places

Short Text

MANDT

CLNT 3 0 Client

SPRAS

LANG 1 0 Language Key

MATNR

CHAR 18 0 Material Number

MAKTX

CHAR 40 0 Material Description

Table 9.2: MARA fields for ZMATERIAL Text

9.1. Creating Views in R/3First we need to create two views: ZMARA_ATTR Master data and ZMARA_TEXT for texts.

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To create a view for the master data, run the transaction SE11, enter a name for the object, select the views option in the Dictionary objects block, and then click .

Figure 9.1: ABAP Dictionary: Initial Screen

Select the Database view option and then click .

Figure 9.2: Choose View Type

The view consists of one table MARA. Enter this name in Table/Join Conditions tab page and in view fields, enter all the fields of table 8.1.

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Figure 9.3: Maintain View

Then save, check and activate the view.

Similarly, you create ZMARA_TEXT. Refer to table 8.2 for fields.

To link the text with the master data, the field MATNR of the table MARA must be equal to the field MATNR of the table MAKT.

9.2. Creating DataSource in R/3.

Run transaction SBIW and click Maintain Generic DataSource, or you may run transaction RSO2.

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Figure 9.4: Maintain Generic DataSource

You select in the above screen. The next screen is displayed

Figure 9.5: Create DataSource

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You enter a name ZMARA_ATTR as the name of the DataSource and then click . The next screen is displayed. Enter all the details in

this screen.

Figure 9.6: Save DataSource

Save the DataSource ZMARA_ATTR as local object. On saving a new window is displayed, check Material Number and click the DataSource.

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Figure 9.7: DataSource: Edit

Note: To test extract, go to menu DataSource->Start Extraction (F8) or click on . After extraction to see the output list again go to menu DataSource->Output list or click .

Similarly, you create ZMARA_TEXT DataSource.

Once you have created ZMARA_ATTR and ZMARA_TEXT DataSources, the next step is to replicate these DataSources in the SAP-BW, so that identical structures of the DataSources are created in BW system.

Next step is to logon to SAP-BW system. Go to Modeling->Source System and right click D47 Client 107 and select Replicate DataSources. As in the figure

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Figure 9.8: Replicate DataSources

Upon Replicating DataSources, double click on P08 Client 107 another window is displayed as shown in the figure.

Figure 9.9: DataSource is replicated

Now you need to create a characteristic ZMARA. Table 9.3 shows the attributes of the characteristic ZMARA.

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Characteristic

Attribute

Compounding

ZMARAMTARTMATKL

Table 9.3 Characteristic ZMARA Master Data

Note that the replication of DataSources from the source system SEND001 has already determined the client from which to extract.

9.3. Loading Data from R/3 into BW

To load the Master data and text follow the same steps discussed in the earlier chapter. However, you need to assign DataSource(s) ZMARA_ATTR for characteristic ZMARA and for texts choose ZMARA_TEXT.

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10 Logistics Cockpit10.1. What is Logistic Cockpit (LC)?

The Logistics Customizing Cockpit is the central administration tool for extract structures. You use it to transfer Logistics transaction data from the OLTP system into the BW system. The extract structures are filled by the R/3 communication structures of the individual Logistics applications. It’s a new technique to extract logistics information and consists of a series of a standard extract structures (that is, from a more BW perspective, standard datasources), delivered in the business content

For extracting logistic transactional data from R/3, a new generation of datasources and extractors, no longer based on LIS (Logistic Information System) information structures, was developed starting from BW Release 2.0B and PI 2000.1 or PI-A 2000.1 (valid from R/3-Release 4.0B ). The tools for the logistics extract structures can be found in the IMG for BW (transaction SBIW (see Fig.1. below)): access into your OLTP system, choose Customer-Defined DataSources -> Logistics -> Managing Extract Structures.

The Cockpit contains the following functions:   Maintaining extract structures Maintaining DataSources   Activating updates   Controlling updates

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10.2. Logistic Cockpit Functions

Fig.1: SBIW

With the LC, several data structures are delivered and, for each level of detail, there exists an extract structure as well as a datasource (that already represents a BW extract view).

When you create and save a sales order (as other transactional tasks), the document is processed in the memory and then stored into application (and database) tables. In LC extraction technique (see Fig.2) we have at our disposal different LIS communications structures (like the MCVBAK, MCVAP, MCVEP and so on for sales orders) that we can decide to use for our reporting purposes when the application is running and during memory processing.

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Fig.2: LC Delta Process for Sales Order Schedule Lines

2LIS_11_VASCL is the standard LC datasource to extract order schedule lines related information. MC11VA0SCL represents its linked extract structure. Remember that it’s possible to enhance that, but you can’t create new extract structures (on the same standard datasource). Within LC (LBWE) (see Fig.3) a tool is provided that enables you to add fields from the LIS communication structures (to the extract structure) without having to do any modifications.

Fig.3: Logistic Cockpit customizing screen

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In the maintenance screen (see Fig.4), on the left side, you see what has already been selected in the standard extract structure and on the right side, you see all the available fields of the communication structures where you can select fields from for the update.

Fig.4: Maintenance screen

It’s enough to highlight the row and click on the left-arrow: (every) selected field is included automatically in a generated append structure for the corresponding include structure of the extract structure When you successfully complete this step, the traffic light icon turns red. This indicates that you changed the structure.At this point, you have to generate the datasource (see Fig.6): here you can (among the other things) choose fields that can be selected .For various reasons, it is not possible to offer all the fields contained in the LIS communication structure for selection in the extract structure; these fields are hidden It is also possible that a key figure is inverted (refer to OSS Note 382779 ‘Cancellation field in the datasource maintenance’ for details).

After maintenance in this step, the traffic light turns yellow.

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Fig.5: Datasource generation

Once you activate the update, data is written to the extract structure and the traffic light then turns green. Our enhancement process is completed and now you can schedule (if required by your delta method) the delta job control process. I.e. select the job control process given below and schedule the job providing the start date and print parameters at the required frequency (see Fig.6)

In fact, scheduling timing process is very important and it should be based on the basis of

1) The amount of activities on a particular OLTP system and on E.g. A development system with a relatively low/medium of new/modified/deleted documents may only need to run the V3 update (explained later) on a weekly/daily basis. Instead, a full production environment, with really many thousands of transactions everyday, may have to be updated hourly; otherwise postings will queue and can affect performance heavily.

2) The particular requirements related to the updating needs of data displayed in BW reports.

e.g. If the reporting timing refers to a monthly periodic view, successfully monthly scheduling the V3 update will ensure that all

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the necessary information structures are properly updated when new or existing documents are processed in the meanwhile.Finally, the right choice will be the result of all these considerations; by doing so, the information structures in BW will be current and overall performance will be improved.

Fig.6: Scheduling the control job

One the job gets scheduled the records get pulled into the delta queue (RSA7) in the OLTP system. This will be the source for delta requests emerging from the corresponding BW system.

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Fig.7: Delta Queue

11 Reporting and Analysis11.1. SAP BW Business Explorer

The Business Explorer (BEx) is a SAP BW component that provides flexible reporting and analysis tools that you can use for strategic analysis and supporting the decision-making process in your organization. These tools include querying, reporting and OLAP functions. The BEx enables a broad range of users to access SAP BW information: Using the Enterprise Portal, Intranet/Internet {Web Application Design) or using mobile end devices WAP or I-mode enabled mobile telephones, and personal digital assistants).

The following is an overview of BEx functional areas:

Figure 9.1: BEx Functional Areas

11.1.1. Query, Reporting, and AnalysisThe data basis of SAP BW is divided into self-contained business data targets (InfoProviders). You analyze the data basis of SAP BW by defining queries for data targets in the BEx Query Designer. You can determine the way in which the data from your chosen data target is analyzed by selecting and combining characteristics and key figures or reusable structures in a query.

Data analysis based on multi-dimensional data sources (OLAP reporting) allows you to analyze more than one dimension of an InfoProvider (for example, time, place, and product) at the same time. This means that you can make any number of variance analyses (plan/ actual comparison and business year comparison). The data, which is displayed in the form of a pivot table, serves as the starting point for a detailed analysis, used to answer a myriad of questions. Numerous interaction options such as sorting, filtering, swapping characteristics, recalculating values, and so on, allow you to flexibly navigate in the data at run time. You can also visualize

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the data in graphics (bar charts or pie charts, for example). You can also evaluate data geographically (for characteristics such as customer, sales region and country) on a map. Moreover you can use Exception Reporting to determine variant and critical objects, to automatically send messages about variant values via email or SMS (through background processing in the Reporting Agent), or to instantly detect such objects in an alert monitor.You can analyze data in the following areas in the SAP BW BEx: . BEx Analyzer (Microsoft Excel based) . In BE Web Applications Both are seamlessly integrated. In other words, you can display queries from the BEx Analyzer in a standard view in the Web browser with a single click. The opposite is also possible, that is, you can export a Web application into Microsoft Excel 2000.

11.1.2. Web Application Design

Web Application Design allows you to implement generic OLAP navigation in Web applications and in Business Intelligence cockpits for both simple and highly individual scenarios. These scenarios can be created using customer-defined interface elements using standard markup languages and Web design APIs. Web Application Design encompasses a wide spectrum of interactive Web-based Business Intelligence scenarios that you can modify to suit your requirements using standard Web technology.

You can use the BEx Web Application Designer, the desktop application for creating Web applications, to generate HTML pages that contain SAP BW specific content such as various tables, charts or maps. You can have the Web applications as URLs and access them from the Internet, Intranet, or mobile devices. You can also save Web applications as iViews and integrate them into an Enterprise Portal.

An assistant, the Web application wizard, has been integrated into the Web Application Designer to support you when creating Web applications. It uses an automatic step-by-step procedure and a simplified design process.

11.1.3. Formatted reporting

The integration of Crystal reports into SAP BW enhances the BEx functional area by allowing you to create formatted reports. Formatted reports mainly involve pixel-precise layout design and user-friendly printing options.

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11.1.4. Mobile intelligence

You can use BEx Mobile Intelligence to call up the Web applications you have created with the Web Application Designer. You can even do this when away from your desk. The following devices are supported:

Personal digital assistant (PDA) with Windows CE 3.0 and Pocket Internet ExplorerWAP-enabled mobile telephonei-Mode-enabled mobile telephoneMobile device with EPOC32 operating system (the Nokia Communicator 9210, for example)

11.2. Working with BExUsing the SAP BW reporting functions, you can evaluate a dataset from an InfoProvider according to various characteristics and key figures. To do this, you define a query for your chosen InfoProvider in the BEx Query Designer.

You have various options for calling up the Query Designer:. From the BEx Analyzer open dialog box. As a separate program using Start Programs Business ExplorerQuery Designer. Using the Web Application Designer (see the BEx Web ApplicationDesigner unit). With Crystal Reports

11.2.1. Functions of the BEx Query DesignerThe following graphic gives an overview of the BEx Query Designer functions that you can call from the Query Designer toolbar. The functions are described within the context of query definition.

Quit and Use Query: With this function, you leave the Query Designer and use the query you have defined.

Exit Query: Choose Exit Query if you want to leave the Query Designer. Your entries are not saved.

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Display Query on the Web: Using this function, you can display the query in a default view on the Web, once you have saved your query definition.

New Query: Choose this function if you want to create a query. The BEx Open dialog box appears and you can select the InfoProvider here that contains the data that you want to evaluate in the query.

Open Query: This function takes you directly to the BEx Open dialog box. The, you can choose from queries in your History, Favorites, Roles, or from the InfoArea.

Save Query: You use this function to save a modified query under its current name. If the query does not yet have a technical name, the system automatically offers the function Save Query As....

Save Query As...: You use this function to save a query under a new technical name. You can save the query in your favorites or in a role.

Delete Query: You use this function to delete the query. You can only delete the query if it is not being used in workbooks, Web templates, Crystal Reports, or reporting agent settings.

Exception: You use this function to define exceptions for a query.

Note: Exceptions are deviations from normal key figure values, as defined by you, and are highlighted in color in the query view. Using the small arrow next to the exceptions symbol, you can change or create exceptions. For more information, see the Exceptions and Conditions unit.

Condition: You use this function to define conditions for a query.

Note: For each characteristic, you can give limit conditions to the key figure values, in order to determine, for example, all sales revenues above or below a specified threshold value. The chosen characteristics are displayed in the query with restricted key figures. Using the small arrow next to the conditions symbol, you can change or create conditions.

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Define Cells: This function is only available for queries with two structures. You can define formulas and selection conditions for cells explicitly. In this way, you control the values of cells that appear at the intersections of structural components. This function enables you to access individual cells in queries or to assign special values to these.

Query Properties: Choose this function if you want to change the description of the query or define the settings for the result position, display options, numeric display, zero display, and key date of the query.

Check Query: Using this function, you can check a new or saved query for errors before you save it.

Query Where-Used List: Using this function, you can find out in which objects (workbooks, Web templates, Crystal Reports, or reporting agent settings) the query is used.

Display <-> Change: Using this function, you can switch between the display and change modes.

Change Query (Global Definition): You choose this function if you are in the Local Query Definition and want to switch to the Global Definition.

Table Display: You can create a query for tabular reporting, as well as for Online Analytical Processing (OLAP) reporting, by activating or deactivating the Table Display mode in the query definition when defining a query. This function is only available for queries with one structure. You can only have queries with two structures in the multi-dimensional display. They are not suitable for OLAP reporting.

Technical Name: Using this function, you can show/hide the technical names of the query components.

Context Menu: This function enables you to display the current context menu without using the right mouse button (for example, for use with a touch screen).

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Help: This function takes you to the SAP BW online documentation. The BEx Query Designer section is displayed automatically there in the BEx documentation.

Using the small arrow next to the help symbol, under the About... entry, you can see the version of the Query Designer, with the support package number and the revision.

11.2.2. Creating a QueryTo define a new query, start the Query Designer and choose New Query. In the New Query: Select InfoProvider dialog box, select the required InfoProvider.

Figure 9.2: New Query: Select InfoProvider

Once you have selected the InfoProvider, the Query Designer is displayed as shown in the following graphic.

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Figure 9.3: Query Designer : New Query

The Query Designer is divided into six sub areas:1. Directory tree of the selected InfoProvider.Once you have selected the required InfoProvider, all available objects (dimensions, key figures, structures) are display in the directory tree in the left screen area of the Query Designer.

2. ColumnsYou define the columns of your report in this area.

3. RowsYou define the rows of your report in this area.

4. Free CharacteristicsYou transfer those characteristics into the free characteristics areas that are not displayed in the first instance when you execute the query in the BEx Analyzer or one the Web. You can then integrate these characteristics through navigation steps. You can also use free characteristics for selecting filter values in the report.

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5. FilterThe characteristics displayed in the filter appear neither in the drilldown nor as free characteristics in the query analysis. These characteristics are only used as global filters on the cube data.

6. Preview (displayed in gray on the screen)This area gives a preview of the query results area. To create a query, you can expand or collapse the InfoProvider directories by clicking on the plus or minus symbol. By expanding the key figure node in the InfoProvider tree, for example, you can display a list of all the key figures for the InfoProvider.

Use Drag & Drop or Choose CTRL C + CTRL V to transfer the characteristics, key figures, and structures of the InfoProvider into the Filter, Rows, Columns, or Free Characteristics areas of the Query Designer.

The following graphic shows the Query Designer with a query definition.

Figure 9.4: Query Definition

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Once you have defined a query, choose Save Query or Save Query As... . If you have not yet saved the query, you have to enter a query description and a unique technical name. You can also choose where you want to save the query (in your roles, favorites). You can use Save Query As... to save existing queries under a different name.

Figure 9.5: Save Query

Once you have saved the query, you have the following options: You can execute the query in the BEx Analyzer and include it in a

workbook. To do this, choose Quit and Use Query. You can display the query on the Web in a default view. To do

this, choose Display Query on the Web. You can use the query in the Web Application Designer as a data

provider for Web items.

11.3. BEx Analyzer

Once you choose Quit and Use Query from the Query Designer, a report is displayed in Microsoft Excel sheet. The report contains the query description, a filter area and the result area. The filter

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area contains the characteristics and free characteristics chosen in the query definition.

Figure 9.6: A Report in BEx Analyzer

11.3.1. Navigation within BEx AnalyzerThe context menus available at various cells allow you perform operations like Sort, Filter, Drill Down, Drill Across, and Remove Drill down etc. that help to analyze the data. The characteristics can be displayed as only Key, or only Name, or both. You may use short or long descriptions for the characteristics. The analyzer allows you to navigate back once you perform such operations.

IF you do not want to display the values for a characteristic choose Remove Drilldown from context menu for that characteristic in the filter area.

Drill Across option allows you to display the values of a characteristic in columns.

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11.3.2. Saving query as a workbookYou may save the generated report as a workbook using either of the following options – Click on the Save button and then choose Save as new workbook …Choose the menu path, Business Explorer Save Save as new workbook…

Workbooks are used if we require more formatting options and need to perform complex calculations (E.g. Using VBA Micros etc).

11.3.3. Changing the query

Depending on your current position in the Query Designer or Analyzer, you have different options for changing a query:

If you have called the Query Designer, in the SAP BEx Query: Choose Query, select a query.

You have two options for changing the query definition from a report in the Analyzer: Choose Change Query (Global Definition) : By doing this, you can

change the query definition. Choose Change Query (Local View): Changes made to the query

here correspond to navigation in the report and are not saved in the query definition.

11.3.4. Filtering Data in the Query DefinitionIt is often necessary to restrict (filter) characteristics to specific characteristic values in your reports. For example, if you are interested in the sales volume of a particular branch of a world-wide corporate group, but the InfoProvider contains the sales volume for the entire organization, you can restrict the query definition to the relevant branch, so that only the key figure for this branch appear in the report.

You can restrict (filter) the characteristic values of a characteristic in the Rows, Columns, Free characteristics, and in the Filter.

There are two ways of restricting characteristics: By selecting a characteristic from the InfoProvider of the

characteristic (in the tree structure in the left part of the screen) and double-clicking on the values icon, the selection menu for fixed values is displayed. You can select single values or values from a value area. The fixed values selected appear in the

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directory tree under Values. You can use Drag & Drop to include these in your query definition.

You can also restrict a characteristic that you have already included in the definition. Call the context menu for the characteristic and choose Restrict. The Selection for ... dialog box appears. The following graphic shows the selection dialog box for the Material characteristic.

Figure 9.7: Filtering data

A restriction on a free characteristic affects the entire query, even if the free characteristic is not in the drilldown.Characteristics in the global filter appear neither in the drilldown nor as free characteristics in the analysis. You cannot navigate in the analysis using the characteristic values in the filter. These characteristics are only used to filter the data from the InfoProvider.

11.3.5. Including Text Elements in BEx Analyzer Reports

You have the option of displaying different text elements as additional information in a query (for example, the author, last changed by, InfoProvider, etc.). These text elements are referred to as the header information of the query.. Choose Layout and Display Text Elements.. You can either display all or individual (General, Filters, Variables) text elements. The text elements are displayed between the filter

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area and the results area. You can move or delete individual text elements by moving or deleting the corresponding cells in Microsoft Excel.

Author: User who defined the query. Last Changed by: User who last changed the query definition.

Navigation steps are not recorded as changes to the definition. InfoProvider: InfoProvider whose data is evaluated in the query.

Query Technical Name: Technical name that you entered when you saved the query.

Key Date: Contains the date for which the time-dependent master data is selected. You create a key date either in the query definition (query properties) or provide the value using a variable (for more information, see the Query Properties unit). If no key date has been defined, the system date is taken as the key date.

Changed At: Date and time at which the query definition was last changed.

Status of Data: Time at which the data from the last request was posted to the InfoProvider. This can be evaluated for reporting.

Current User: User who currently has the query open or who has inserted it into a workbook.

Last Refreshed: Data and time at which the query data was last refreshed. This is the time at which you displayed the text elements (the system has to refresh the query in order to display the text elements).

Variables, Filter Values, Conditions, Exceptions: Depending on the current query definition, additional text elements (variables, filter values, conditions, and exceptions) may also be displayed.

11.3.6. Properties of Key FiguresThe various components of a query have specific properties that reproduce important functions. You call the properties dialog box from the context menu for the key figure for which you want to define properties, by selecting Properties.In the Properties of the Selection/Form dialog box for a structure part, you can set a range of functions.

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Figure 9.8: Properties of Key Figure

Description: You can change the automatically determined key figure description here (basic key figure, restricted key figure, calculated key figure) here.

Technical name Display: You can assign a unique technical name to structure

parts such as key figures. This is optional. You can choose whether the key figure is to be highlighted in the report here. You can hide key figures that you only need for calculating formulas, and do not want to display in the analysis. You can also mark as selection as constant so that this selection can no longer be changed by navigation and filter at runtime.

Number Display: You can set the scaling factor in the Number Format area. Caution: The scaling factor is not automatically displayed in the report. You have to set the scaling factor display

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separately in the query properties. You can define the number of decimal places here and reverse the +/- signs. The reverse +/- signs is only a display function. It has no influence on calculation in formulas.

Calculations: You can use this function to recalculate result rows and individual values that are displayed in the version according to particular criteria. E. g. You want to calculate the result on the basis of the average of all displayed sales volumes instead of on the basis of total sales volume.

Currency Translation: In the Query Designer you can set a currency conversion key and a target currency in the properties dialog box for a structure part.

11.3.7. Properties of Characteristics

The various components of a query have specific properties that reproduce important functions. You call the properties dialog box from the context menu for the characteristic for which you want to define properties, by selecting Properties.In the Characteristic Properties dialog box, you can make settings for a range of functions that affect the key figures for this characteristic in the query drilldown.

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Figure 9.9: Properties for a Characteristic

You can define the following properties for characteristics: Description: The text provided in the InfoObject maintenance

appears here. You can change the text and display it in the query.

Display As: This is where you determine the form in which the characteristic values are displayed, as long as they were created in the InfoObject maintenance for the characteristic:

No DisplayKey and NameName and KeyNameKeyLong or Medium NameDisplay of Results

Suppress Results Rows: You can structure the appearance of your report by using this function to determine whether the results rows are displayed Always, Never or With Only One Value.

Normalized to: You can use this function to normalize key figure values to a specific characteristic. When values are normalized, the key figures are displayed as a percentage in relation to the chosen result. You can select the Query Result, Overall Result and Result (interim result) as the reference value. The characteristic is normalized only if it is in the drilldown.

Cumulative: This function aggregates the values of the characteristic values (the nth value is aggregated with the n+1 value).

Sorting: You can make settings for sorting within the characteristic. You can use the following:

The characteristic itself, sorted by key or name,All attributes of the characteristic sorted by Key or NameThe sort sequence is either Ascending or Descending. You cannot use the attribute that you have selected for sorting in the display.

Display Hierarchy: You can display the characteristic hierarchically. You make the necessary settings for this here.

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11.3.7.1. Attributes Characteristics can be described in more detail through attributes. For example, you can assign the attribute Telephone Number to the characteristic Sold-to Party to display the telephone number of the sold-to party.You assign attributes to characteristics in the InfoCube maintenance. You can maintain them as purely Display Attributes or as Navigation Attributes.

You can show Display Attributes in a report in the drilldown. However, navigation steps are not possible. (For example, you cannot choose values from a display attribute as a filter.) To include a display attribute in the drilldown, open the index for the characteristic. Once in the Attributes index, drag the required attribute into the query definition.To select a display attribute of a characteristic that is already in the query definition, from the context menu of the characteristic, choose Attributes. In the Attribute Properties for a specific attribute for a characteristic, you can set the display functions as key, name, and so on.

You can use Navigation Attributes for defining queries in reporting in the same way as characteristics. They are displayed in the dimension of the characteristic to which they belong.

In order to use an attribute as a navigation attribute, note the following:1. You have to flag the attribute as a navigation attribute in the InfoObject maintenance of the characteristic.2. You have to select that attribute from the list of possible navigation attributes in the InfoObject maintenance.Note the following when using navigation attributes:. Time-dependency of the navigation attributeNavigational attributes enable you to view current data with characteristic values from the past or view past data with current characteristic values.. Navigation attributes used as characteristics.. Slight loss in performance in comparison with using characteristics.

11.4. Restricted Key FiguresRestricted key figures are (basic) key figures of the InfoProvider that are restricted (filtered) by one or more characteristic selections. The key figure that is restricted by one or more characteristic selections can be a basic key figure, a calculated key figure, or a key figure

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that is already restricted. By using restricted key figures, you can focus the query result on certain values. Unlike a filter, whose restrictions are valid for the entire query, for a restricted key figure, only the key figure in question is restricted to its allocated characteristic value or characteristic value interval. Scenarios such as comparing a particular key figure for various time segments, or plan/actual comparison for a key figure if the plan data is stored using a particular characteristic, can be realized using restricted key figures.

11.4.1. Defining Restricted Key Figures

You can create restricted key figures at InfoProvider level, or locally in the query definition. Restricted key figures that are defined at InfoProvider level are available in every query definition of the InfoProvider in question.

1. To define a restricted key figure at InfoProvider level, from the Query Designer choose Restricted Key Figure in the context menu on the left-hand side under Key Figure.To define a restricted key figure at query level, use Drag &Drop to drag the key figure to be restricted into a Query Designer directory. In the context menu, choose Edit, or select the heading of the Rows or Columns directory and use the secondary mouse button to choose New Structure. Select the structure directory and use the secondary mouse button to choose New Selection from the context menu. The New Selection dialog box appears.

2. Enter a description of the restricted key figure into the text field.3. If another key figure was selected, use Drag & Drop to choose

the key figure of the InfoProvider, and place it on the right-hand side of the Selection window

4. Use Drag &Drop to move the characteristic whose characteristic value you want to use to restrict the key figure to the right-hand side of the Selection window.

5. From the context menu of the characteristic, choose Restrict.6. Select the characteristic values you require for the restriction.7. Confirm your entries by choosing OK.8. For the definition at InfoProvider level, you enter a technical

name in the dialog box, and confirm your entry by choosing OK. The newly defined key figure can be found in the Restricted Key Figures directory. In the case of definition at query level, the new restricted key figure is already part of the structure.

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11.4.2. Selection Conditions for the Selection of Filter Values

When defining a restricted key figure, you want to select the restricting characteristics, individual characteristics values, value ranges, hierarchy nodes, or characteristic variables. When selecting value ranges, the following operations are available:

Between Greater than or equal to Less than or equal to Greater than Less than

The following figure shows the definition of a restricted key figure, which will give the Sales amount only for year 2002.

Figure 9.10: Defining a Restricted Key Figure

The following is a snapshot of a report, which uses the restricted key figure defined above to compare overall sales with the sales made in year 2002.

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Figure 9.11: A Report with a Restricted Key Figure

11.5. Calculated Key FiguresIn the Query Designer, you can use a formula to calculate key figures that are not in the InfoProvider by using basic key figures, restricted key figures, and existing calculated key figures in the formula definition.Defining Calculated Key FiguresYou can use all basic key figures of the InfoProvider in question, as well as the newly defined restricted and calculated key figures of the InfoProvider, to define new calculated key figures. You can define calculated key figures at both query level and InfoProvider level. At query level, the calculated key figure is valid only for the query in question. If you create a calculated key figure at InfoProvider level, you can use it in all queries that are based on the same InfoProvider.

11.5.1. Defining Calculated Key Figures at InfoProvider Level

1. Select the Key Figure directory, and choose New Calculated Key Figure from the context menu. You reach the New Calculated Key Figure dialog box.2. Enter a description of the calculated key figure into the text field.3. Define the required formula using basic key figures, restricted key figures, formula operators, and functions. You can use Drag & Drop to transfer the formula components into the formula field.Key figures always have the same units when a query is executed. This means that the formula is semantically incorrect if you add a currency unit (for example, EUR) to a unit of weight (for example,

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kg). If you want to calculate values without using units, you should use the Value Without Dimension function. See Data Functions.4. Check the formula definition, and choose Formula Syntax Check.The Formula Syntax Check function only checks the syntax of the formula. It does not check whether the formula is semantically sound, for example, whether the units are compatible.5. Choose OK. In the Properties of the Calculated Key Figure dialog box, assign a technical name, and choose OK. If you choose Enhance, the dialog box is enhanced with aggregation behavior or exception aggregation options.6. The new calculated key figure is available under Calculated Key Figure, and can be included in the definition using Drag & Drop. To define calculated key figures, you have to include key figures needed for the calculation in the definition, and choose New Formula from the context menu of the Key Figure directory. These formulas are available only locally in the query definition. If you are defining calculations in the columns as well as in the rows, a formula collision can occur in the interfaces of the two formulas. You can therefore define which of the formulas is to be used.

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Figure 9.12: Defining a Calculated Key Figure

The following snapshot of a report shows the use of the calculated key figure defined above.

Figure 9.13: A Report with a Calculated Key Figure

11.6. VariablesFor flexible reporting we often need variables. Variables are query parameters that you define in the Query Designer and that are filled with values only when you execute the query or Web application.

Variables act as placeholders for:. Characteristic values. Hierarchies. Hierarchy nodes. Texts. Formula elementsVariables are reusable objects.The variables defined in the Query Designer are available in all InfoProviders for use in query definition. Variables are not dependent on the InfoProvider, but rather on the InfoObject for which they were created.Variables enable you to set queries more flexibly (query parameterization).When using variables in the Query Designer, you do not choose fixed characteristic values, hierarchies, hierarchy nodes, texts, or formula elements, but rather you set variables as placeholders. These are then filled with values at query runtime (when you insert the query into a workbook, when you refresh a workbook or when you launch the query on the Web). If you use variables, a query definition can then serve as the basis for many different queries.

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Variable TypesThere are different variable types, depending on the object (for example, characteristic, formula) for which the variable is defined as a placeholder.

Characteristic Value VariablesWhen selecting characteristic values in the query definition, you can select variables instead of fixed values. These act as placeholders and are filled with values when you execute the query. You can use variables to select single values and value areas.

1. Selecting Single Value VariablesFrom the context menu of the characteristic, choose Restrict. The dialog box for selecting characteristic values appears. Select the Variables tab page and transfer the required variables using Drag & Drop or the arrow button.

2. Selecting Single Value Variables as Variable Value Area LimitsIn the dialog box for selecting characteristic values, in the Selection field, choose Value Area and set the required operator (Between, Less than, Greater than, ...).Select the Variables tab page. When using the Between operator, you can restrict both limits using single value variables or choose a single value variable for one of the interval limits and transfer a fixed value for the other interval limit on the Fixed Values tab page.

When using the operators Greater than or equal to, Less than or equal to, Greater than, or Less than, from the list of available variables in the left window, highlight a variable and move this using Drag & Drop or the arrow button into the right Selection window.

Swapping Interval LimitsIf you are using variables when making interval selections, you can swap the limits by highlighting the relevant variable in the right Selection window, and choosing Swap Interval Limits from the context menu.

3. Selecting Variables with Several Single Values or Value RangesDepending on how they have been defined, you can not only select single values for variables, but also several single values, intervals, or selection options. Under Single Values select the relevant variable from the variables window and specify the values or interval limits when you execute the query.

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Variable Processing TypesThe following processing types are available:User Entry/Default ValueReplacement PathCustomer ExitSAP ExitAuthorization. User Entry / Default ValueIf you choose User Entry/Default Value as the processing type for a variable, you can enter the required value for the variable manually in a dialog box when you execute the query.

You enter a default value when you create the variable. This default value is then displayed for input-enabled variables in the input field of the variable screen. For fields that are not input-enabled, the default value is used as the variable value.. Replacement PathThe processing type Replacement Path enables you to specify the value that automatically replaces the variable when the query or Web application is executed.For example, when you enter a variable as a characteristic value, you do not need to determine the text for the characteristic value straight away, but can let it be filled dynamically to match the characteristic that is used when the query is executed for the variable.1. Text variables and formula variables with the replacement path processing type are replaced by the corresponding characteristic value. The variable wizard takes you through the Characteristic dialog step automatically. This is where you select the reference for the replacement value.2. Characteristic value variables with the replacement path processing type are replaced by a query result. In the Replacement Path dialog box, you select the query containing the results that you want to use as a variable. You can now use the data result of the selected query as a variable in a different query.

. AuthorizationThe Authorization processing type enables you to fill the variables automatically with the values frothed authorization of a user. If you choose the Authorization processing type when you create a variable, the variable is filled automatically with the values in the user’s authorization.

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When the user opens a query, the data selection is automatically carried out according to his or her authorizations.

. Customer exitIf necessary, you have the option of using a customer exit to set up a processing type for variables that is tailored specifically to your needs. The Customer Exit processing type for variables enables you to determine values for variables by means of a function module exit. The function module used is EXIT_SAPLRRS0_001.

You create a project in transaction CMOD by selecting the SAP enhancement RSR00001 and assigning this to the enhancement project. Activate the project. Note: For more information about working with the SAP enhancement for global variables in reporting, see the SAP enhancement help. Call the transaction SMOD. Enter the name of the enhancement (RSR00001), choose Documentation and then Edit Display/Change. For general information about working with Customer Exits, see the Application Help in transaction CMOD.

. SAP ExitThe SAP exit processing type is contained in variables that are delivered with SAP BW Business Content. Overview of Variable Types and Processing Types

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The Variable WizardThe variable wizard takes you through a step-by-step process for defining a new variable.

IntroductionThe first dialog step in the variable wizard explains that instead of defining fixed values for your query, you can define variables as placeholders that are then filled with values at runtime. If you do not want to display this step in the future, put a check in the Do not display this step in future box.

General InformationThe type of variable is shown in the second dialog step. You determine the variable type by calling up the variable wizard in a specific context.

Context-Sensitive EntriesThe following appear differently, according to context:DetailsDefault ValuesReplacement Path

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CharacteristicCurrencies and Units

DetailsA dialog step in the variable wizard in which all types of variables appear except for variables with the replacement path processing type.

The variable wizard automatically offers you only those options that are possible and useful.

Figure 72: Variable Wizard: DetailsUnder Variable Represents, select the display area that the variable is to represent. You can choose from:. Single ValueThe variable represents one value only.. Multiple Single ValuesThe variable represents a range of single values.You can use this setting with hierarchy nodes, for example, to enable the user to enter several single nodes.. IntervalThe variable represents a from-value and a to-value.. Selection OptionThe variable represents a combination of single values and intervals of your choice.. Precalculated Value SetThe variable represents a number of values that are stored in a database table by the Reporting Agent.2. Under Variable Entry is specify whether the variable input is Optional, Mandatory, or Mandatory, Initial Value not Allowed.

3. Under Ready for input you can determine whether the variable is input-enabled when the query or Web application is executed. If the ready-for-input option is active (= default setting), the variables screen is offered when you execute the query or Web application. You can then enter the required values, confirm the default values, or change the default values.

4. The option Can be changed in query navigation enables you not only to select from values that you entered in the variables screen after you have executed the query, but also use other values as dynamo ic filters in the query.

5. Copy personalization data from variable

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You can personalize variable values for input-enabled variables for each user. These personal values are saved for each variable and each user.

Default ValuesWhen you define a variable, you enter one or more default values. These then appear in the variables screen when you execute the query or Web application.

Replacement PathA dialog step of the variable wizard that appears for characteristic value variables, formula variables, and text variables with the replacement path processing type.

There are different options for the replacement path, according to the type of variable used:. Text variables and formula variables with the Replacement Path processing type are replaced by the corresponding characteristic value.

The value for a formula variable has to be a number. The value for a text variable has to be a text.1. Under Replace Variable With, you have the following options:KeyExternal Characteristic Value of the KeyName (Text)Attribute ValueHierarchy Attribute2. Using the setting With Interval Take, you determine whether the From-Value, the To-Value, or the Difference is used as the value when the value to be replaced is an interval.3. The setting Offset Start and Offset Length enables you to determine the start and the length of the text output.4. The Evaluate as Boolean function (value 0 or 1)This function is only available for formula variables. If you select this setting, the formula variable is not replaced by a value (for example, key value), but rather it specifies that a value exists.

. The value of the variable is 0 if the value to be replaced is a string with only blank characters or a zero.. The value of the variable is 1 if the value to be replaced is a string with characters that are not blank or a number that is not zero.. Characteristic value variables with the Replacement Path processing type are replaced by a query result.

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You can now use the data result of the selected query in a different query using the variable.Example: You want to insert the result of the query Top 5 Products into another query Sales Volume - Calendar Year/Month variably.1. Highlight the characteristic, for example, Product, and from the context menu, choose New Variable. The variable wizard appears.2. Enter a name and a description for the variable and choose the Replacement Path processing type.3. You reach the Replacement Path dialog step. Enter the name of the query (for example, Top 5 Products)4. You reach the Save Variable dialog step.5. You can now insert the variable into the query (Sales Volume – Calendar Year/Month) to determine how the sales volume of the 5 products with the highest sales volumes has developed on a month-by-month basis.Note: Each time that the query Sales Volume – Calendar Year/Month is executed, the pre-query (Top 5 Products) is executed beforehand. This can lead to long runtimes. If you do not absolutely need to execute a pre-query (for example, you do not have to calculate the top 5 products every time since these change only monthly), we recommend that you use a variable that represents a precalculated value set.

CharacteristicA dialog step of the variable wizard that appears for text and formula variables with the Replacement Path processing type. In text and formula variables with the Replacement Path processing type, the characteristic reference is not clear in the system. Therefore, select the characteristic to which the variable refers.

Currencies and UnitsA dialog step of the variable wizard for formula variables.You can select from the following dimensions:AmountQuantityPrice (= currency/unit)Number (= default setting)DateSaving VariablesIn the final dialog step, you get an overview of the settings you have made for the variable. Choose Finish. The variable is saved and the variable wizard closes.

Changing Variables in the Variable Editor

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The variable editor uses a dialog box to give all of the selection options available for changing an existing variable.

The individual fields of the dialog box reflect the dialog steps in the variable wizard and show the current settings of the variable. The dialog box is context sensitive, which means that only the fields and options that are relevant for the variable are displayed, depending on the type of variable and the processing type. If you would rather make your changes using a step-by-step processes with explanatory text, you can go to the variable wizard.

Using the Variable Offset

To analyze key figures that have a fixed time-relationship to one another, you can use the variable offset. For example, you want to compare the sales volume from the current time period with that of the same time period in the previous year. In your report definition, you can use the same variable several times to restrict the key figures and determine a difference from the input value.You can also use the variable offset to select an interval as a restriction with upper and lower limits that refer to the same variable.1. To do this, in the upper-left selection field, choose Value Range and Between as the operator.2. On the Variables tab page, select the required variable and move this using Drag & Drop (or using the arrow key pointing to the right) into the right selection window.3. Now specify variable offsets for the upper and lower limits.

Selecting Variable OffsetsThis function is only available for characteristic value variables of the type single value or interval.1. Select the relevant variable from the right Selection window.2. Using the right mouse button, call the context menu and choose Specify Variable Offsets.3. In the Variable Offset dialog box, enter the required variable offset. When using value ranges, specify the variable offset for the upper and lower limits.

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11.7. Content VariablesBusiness Content variables are delivered for all types of variables. You have to activate the variables delivered before you can use them. Variables that are delivered with Business Content from SAP BW often have the SAP exit processing type. This enables you to create complex queries quickly and easily.

For time characteristics, a range of variables are delivered that replace frequently used time periods or specific times, for example, the current month or the comparable month of the previous year.

In the Metadata Repository, you find the variables that were created for the InfoObjects used. You also find information about whether the variable in question is actively available in the system.

11.8. ExceptionsThe readability of a report improves if the threshold values are shown with different colors. This is done using Exceptions on a query level.

The functions in exception reporting enable you to select and highlight unusual deviations of key figure values in a query. You can see deviations from pre-defined threshold values or intervals in the query result displayed in different colors if the exception is active. Spotting these deviations early provides the basis for timely and effective reactions.

11.9. Creating ExceptionsYou create an exception in the Query Designer using the symbol Exception New Exception.

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Figure 91: Defining Exceptions in the Query Designer

In the dialog box that appears, you can specify a meaningful Description and set the exception to Active. The exception is applied as soon as you execute the query. If you do not set the active flag, you can activate the exception in the report itself. In the BEx Analyzer, from the BW toolbar Layout Display Exceptions you also have the option of adding an additional line between the filter and results areas for each exception and activating or deactivating the exception from there. There is an item for Web applications that you can integrate into your template for the same purpose. You can use exceptions to evaluate one or all key figures in your query definition. If you want to use exceptions selectively on specific key figures in your query definition, you have to define an exception for each key figure accordingly.

11.9.1. Exception ValuesOn the Exception Values tab page, you enter your values by first choosing New. An alert level row always consists of a From field, a To field and an Alert Level field. If you leave the From or the To value empty, this gives an infinite value definition. You choose Transfer to add your entries to the list of threshold values.

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Hint: You can proceed as follows to make entering large values with many zeros easier:An apostrophe after the value means multiply by a thousand, two mean multiply by a million and three mean multiply by a billion (for example: 1.= 1,000, 1,5..= 1,500,000).

By defining variables as threshold values, you can influence defined exceptions flexibly. You can allocate the available alert levels as you wish. You can set the alert colors red, yellow and green, each in three shades, as required. The colors relate to the color characteristic values of the format templates delivered by SAP and symbolize traffic-light colors.

You can include all values or specific intervals (for example, only those falling below the threshold value in the red area) in the threshold value catalog. You can enter fixed point or floating-point numbers for the values you are defining.

With key figures that exceed the threshold value and are on the border between two intervals, the worst alert level is always shown (for example, interval 0 to 1000 alert level 9 and 1000 5000 alert level 8, the sales volume key figure is 1000 - alert level 9 is used as the basis for identification

Cell RestrictionsOn the Cell Restrictions tag page, you can specify whether a restriction with regard to the use of the exception applies Only to the Totals (default setting) or to All values (therefore not a restriction).

You can choose New to define an operator for each characteristic in the query definition, and a value for each operator. You also choose Transfer here to add your restrictions to the list.

You have the following selection options for the operators:. Everything: The cell context is not restricted. The exception applies for every drilldown state of the characteristic.. Totals Only: The exception affects only the aggregated values of the characteristic.. Everything Except Totals: The exception affects all values except for the aggregated values of the characteristic.. Fixed Value: The exception applies only to a specific characteristic value of the characteristic, which you can determine in the search help in the value field. You can also use a characteristic value variable here. To do this, select Variables Entry. You are then given

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the option of using or changing an existing characteristic value variable, or of creating a new one.

. Level: The exception applies only to specific hierarchy levels of the characteristic. You enter the required hierarchy level in the value field here.

Note that you have to list all characteristics that you defined in the Cell Restrictions in the drilldown of the report, since the exception takes effect only then. If there is a characteristic in the drilldown that is not recorded in the cell restrictions, the effect that the exception has depends on whether you selected Totals Only or All on the Cell Restrictions tab page. If you selected All, it does not matter where you integrate the characteristic in the drilldown, the exception is applied accordingly. However, if you selected Totals Only you have to place this characteristic at the end of the drilldown, otherwise the exception does not take effect.

The following snapshot of a report shows the cells in different colors as per the exception.

Figure x.x : A report with an Exception applied

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11.9.2. Changing and Deleting ExceptionsYou can change exceptions in the Query Designer using the symbol Exception Change Exception. If you want to delete or changing a list entry, highlight the entry using your cursor and choose Delete, or OK if you want to make changes.

You can change exceptions in the Query Designer using the symbol Exception Change Exception. Use the cursor to highlight the exception that you want to delete and choose Delete to confirm. Hint: If you execute your report on the Web, you can create, change, activate and deactivate exceptions using the List of Exceptions Web item. You can delete an exception using the context menu only if you created the exception in the Web application itself.

You can define several exceptions in a query for different value assignment areas or for different versions. If the threshold value areas overlap when you activate several exceptions, the worst (highest) alert level counts.

11.10. ConditionsSometimes it is desired to flexibly restrict a report so that only the most important information is displayed. This should enable a more efficient analysis of data when large amounts of data are analyzed. This is achieved using conditions.

By defining you have the option of analyzing the query results in more detail. You can analyze combinations of characteristics using ranked lists, thereby displaying your ten best customers by sales revenue, for example. By defining value limits you can display all key figure values above or below a certain value. The data is restricted accordingly in the results area of the query, so that you only see the area that interests you. You can define multiple conditions for a query, and then activate or deactivate them in thereport itself to create different views of the data.

11.10.1. Defining ConditionsYou can make restrictions in the Query Designer, using Condition. As a prerequisite, you have to have created a query definition for which one or more conditions can be defined.In the dialog box that appears, you specify a meaningful Description and set the condition to Active. If the condition has the status Active, it is used in the report as soon as you execute the query. If

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you do not set the active flag, you can activate the condition in the report itself. In the BEx Analyzer, from the BW toolbar Layout Display Conditions you also have the option of adding an additional line between the filter and results areas for each condition and activating or deactivating the condition from there. There is an item for Web applications that you can integrate into your template for the same purpose.

You can set conditions for all characteristics, single characteristics and characteristic combinations in the report drilldown, that is, in the results area in the BEx Analyzer or in the table item.

Hint: If you restrict conditions for a report to Single Characteristic or Combinations of Characteristics, you have to ensure that the characteristic or the combination of characteristics is integrated into the report drilldown for the restrictions defined to take effect.

Figure 97: Defining a Condition

11.10.2. FeaturesIn the area Display all values for which at least one of the following conditions applies, you choose New to select a Key Figure for which a condition is to be used. In the second field, you can see the

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operators for specifying value definitions. You choose Transfer to add your entries to the list of conditions and choose New to define more conditions. You save your conditions by choosing OK and you can then display your report in the BEx Analyzer or in the browser.

A condition row consists of a key figure, an operator, and a value for the operator. In query definitions that contain two structures, there is an additional field for defining a structural component.

You can use the following operators for threshold value conditions:: Equal to - Example: Invoiced quantity equals 1000 Not equal to - Example: Line item not equal to 5 Less than - Example: Sales revenue less than 100,000 EUR Greater than - Example: Incoming orders greater than 1,000,000

EUR Less than or equal to - Example: Sales revenue less than or equal

to 100,000 EUR Greater than or equal to - Example: Incoming orders greater than

or equal to 1,000,000 EUR Between - Example: Sales from/to, with the option of defining

these values using a variable request Not Between - Example: Sales from/to excluded from display,

with the option of defining these values flexibly at runtime.

In the variable definition, select Variable Entry. You are then given the option of choosing an existing variable from the dropdown box, changing the variable or creating a New Variable.

You can use the following operators for ranked list functions:. Top N - Example: Display the sales revenue of the top 5 customers. Bottom N - Example: Display the bottom3 (lowest) incoming orders. Top % - Example: Restriction to 20%of the best revenue, in order. Bottom % - Example: List of 15%of the customers with the lowest sales revenue, in order. Top Sum - Example: You get a list of the products with the highest sales revenues where the total sales revenue makes up 20,000 EUR. All sales revenues are sorted in descending order and then the sum is calculated until the threshold value of 20,000 EUR is exceeded. All products, including the product that takes the sales volume over the 20,000 EUR mark, are listed.. Bottom Sum - Example: As with Top Sum but here, a ranked list is sorted in ascending order of products with the weakest sales revenue until a sum greater than or equal to 20,000 EUR is reached. All products, including the product that takes the sum over the 20,000 EUR mark are also listed here.

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The following figure shows a report where only Top 2 Customers according to Sales are displayed.

Figure x.x : A report with a condition applied.

11.10.3. Calculate Result As to display the Summation. If you are using the browser, you can call the context menu and then choose Properties Local Properties Calculate Result As Summation.

11.10.4. Using Several Conditions in a ReportIf you are using several conditions in one report, conflicts can arise which lead to automatic deactivation. The following status descriptions appear in the display:. VariantReason:The condition relates to a characteristic that is not included in the drilldown.The condition relates to a characteristic combination that is not included in the drilldown.. Not UsedReason:The condition relates to a characteristic that is drilled down using an active display hierarchy.

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The condition relates to a characteristic that is included through the activation of another condition, leading to a collision, and is therefore deactivated (however, you can reactivate this condition and automatically deactivate the last condition activated).

If you activate a condition for a combination of characteristics, the results row is no longer displayed.

11.10.5. Changing and Deleting ConditionsTo change existing conditions, in the Query Designer choose Condition Change Condition. The Selection dialog box appears. Highlight the required condition and confirm with OK. In the Define Condition dialog box, you can add new conditions to the list, or highlight existing conditions to change or delete them.

You can also delete conditions from the Selection dialog box by highlighting the relevant conditions and choosing Delete to remove it from the list.

If you execute your report on the Web, you can create, change, activate and deactivate conditions using the List of Conditions Web item. You can delete a condition using the context menu only if you created the condition in the Web application itself.

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12 BEx Web Application Designer

12.1. IntroductionThe BEx Web Application Designer is a desktop application for creating Web applications with BI-specific content. Using the BEx Web Application Designer, you can create an HTML page containing BI-specific content such as various tables, charts, or maps. This HTML page (Web application) forms the basis of Web applications with complex interaction, as well as Web cockpits and iViews. The command wizard and pattern wizard are integral parts of the Web Application Designer. Using the command wizard, you can easily generate commands from the Web Design API and include them in your Web template. Using the pattern wizard, you can configure BI patterns to a certain extent and tailor them to meet your needs.

12.2. FeaturesThe initial view of the BEx Web Application Designer has four different screen areas in addition to the menu and toolbars as depicted in the figure below

●      Web Items Screen Area (1)

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●      Web Template Screen Area (2)●      Errors and Warnings Screen Area (3)●      Properties Screen Area (4)

You can adjust the appearance of the Web Application Designer to meet your requirements. The object on which you are working, namely the Web template, is handled differently from the tools and help windows with which you are working.

●   You can show and hide the individual screen areas and toolbars using the View menu option.

●   You can reposition the three toolbars and the Web Items and Properties windows as required. Depending on where you position the object, it is either anchored or appears freely as a toolbox.

●   Since the Web Application Designer is a Multiple Document Interface Application (MDI Application), you can open and manage different windows with Web templates simultaneously. You can use the Window menu option to arrange the windows differently: cascading (overlapping), vertical, or horizontal.

Web Items Screen AreaThe Web Items window offers a pool of Web items that you can use to create your Web application. A Web item describes the way in which the data from a data provider is displayed, such as tables ,maps and graphics (i.e. Chart).

The Web Items screen area is divided into the following sections: The selection groups for Web items (master Web items) are located in the upper area, divided into various categories:

Standard: The following Web items are part of the Standard grouping: Analysis Chart Report Navigation area Filter area Button group Dropdown box Radio button groups Checkbox group List box Hierarchical filter selection

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Extended: The following Web items are part of the Advanced grouping: Web Template Container Layout Container Tab Pages Group Single Document Document List Map System Messages Information Field Input Field

Miscellaneous: The following Web items are part of the Miscellaneous grouping:

Data Provider – Information Text Link List of Exceptions List of Conditions Menu Bar Properties Pane Ticker Context Menu Script

Web Template Screen AreaThe Web Template window contains the Web templates that you edit in the design process and that form the basis of your Web applications.

Structure

In the upper section of the Web Template screen area, there are three tab pages you can use to change the view of the Web template – in the same way that you do in an HTML editor.

Layout tab pageIn the layout view, you have a visual focus and specify the layout of the Web application. To do this, you use drag and drop to insert Web items from the pool of Web items into your Web template. For more information about other options and

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procedures for the layout of Web templates, see Layout Design of Web Templates and Context Menu in Web Templates.In the lower section of the layout view, you can create data providers. When you double-click New Data Provider, the dialog for creating data providers opens.You can also create data providers in the Web Items screen area.

XHTML tab pageThe XHTML view displays the XHTML that corresponds to the layout view. Each element of the XHTML syntax has a different color.

Overview tab pageOn the Overview tab page, all Web items, data providers, and commands used in Web templates are listed. By selecting or deselecting checkboxes, you specify which of these objects is listed. The objects are listed vertically in the Web Item Name column. In the horizontal alignment of the table, any data providers and reusable Web items associated with the object listed are displayed. Using Sort Order, you can specify how the used objects are to be listed:

o GroupedIf you choose this sort order, the objects used are listed by type: data providers, Web items and commands.

o Web TemplateIf you choose this sort order, the sequence of the objects used in the Web template are displayed as a flat structure.

o Web Template (Hierarchical)If you choose this sort order, the sequence of the objects used in the Web template are displayed as a hierarchical structure. You see a hierarchical structure if you nest Web items in the Web template (for example, when you use the Container Web item).

You can change the parameters of the associated objects using the context menu for each Web item, Web template, and data provider listed

Properties Screen AreaIn the Properties screen area, you define the properties of Web templates and Web items.StructureThe Properties screen area is divided into the following sections:

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In the dropdown box in the header of the screen area you see the selection for which you want to define properties – for a Web template or for specific Web items. Depending on your choice in the dropdown box, you can then make various settings for Web templates or Web items.

Once you have selected a Web template from the dropdown box, you can set the parameters for the Web template on the Web Template Parameter tab page.

Once you have chosen a Web item from the dropdown box, you can make the following settings: Tab page: General

Here you can use the Create New symbol next to the dropdown box to create a data provider and assign it to the Web item. See Web Template Parameters.

Tab Page: Web Item ParameterHere you can set the parameter for the selected Web item.

In the lower area of the Web Item Parameter tab page or the Web Template Parameter Web page, context sensitive help is available.

Errors and Warnings Screen Area

The Errors and Warnings screen area is used to display errors and warnings that are found when a Web template is being verified. IntegrationThe errors and warnings that are displayed in this screen area refer to the following possible checks of the Web template.

VerifyThis check is performed automatically and by default every two seconds. Within the verification, the internal structure of the Web template is checked. You can change the refresh time for the verification in the menu bar under Tools ® Settings.

Verification on the serverWith this verification, which you trigger manually, additional conditions for creating a correct Web template are checked on the server side. Here for example, the system verifies whether a query that is being used as a data provider exists. To trigger the verification, on the menu bar for the Web Application Designer, choose Web Template ® Verify on Server

Correct and formatDuring this verification, which you can trigger manually, the internal structure of the HTML is checked. You can only trigger

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this verification when you are in the XHTML view. From the Web Application Designer menu bar, choose Edit ® Correct and Format.

Under Data Provider, you can create data providers of type Filter or of type Query View. Drag the required data provider type into your Web template using Drag&Drop. The dialog for creating data providers opens.

Underneath the selection for Web items and data provider maintenance, you see the help area, which provides explanations for the Web items and the data providers. To display the texts for the respective Web item, select the Web item by double-clicking with the right mouse button. To hide the texts, proceed in the same way. Once you have hidden the display of texts and selected a Web item by single clicking, a quick info is displayed for the Web item.

Creating A Web Application Using the Web Application Designer

After selecting Create a new web application , you will get a new screen wherein you can add web items from the left of your screen to create a web application. Let us create a simple web application having A table a Chart and a Navigation Block.You can drag and

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drop these elements from under the Standard Web Items pane into the WAD layout.

Select on Create a new data provider and the following window will pop-up

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Browse for a query you have created . We have selected a query created on one of the BW Statistics Cube here YTBD_STATS_QUERY. And select ok.

Select the table in your right hand pane and check the properties tab in your left pane.. Assign the Info provider DP1 to the table. Repeat the same process for the chart and the Navigation block.

Save the Web template and run this web template in the browser.

12.3. Sample Web Dashboards

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Sample Web Dashboard is as shown below:

Web Report in Portal is as shown below:

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Retail Price by Channel - AS