Introduction to BusinessObjects Data Services · PDF fileIntegrate. Manage. Govern. ... SAP...
Transcript of Introduction to BusinessObjects Data Services · PDF fileIntegrate. Manage. Govern. ... SAP...
Introduction to SAP BusinessObjects Data Services XI 3.0
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1. Why Enterprise Information Management2. Data Services: One tool for data integration and data quality
management3. Metadata Management: Impact and lineage to prove trustworthiness of
your data4. Some data services use cases in an SAP environment5. Wrap-up
Agenda
Trusted Information is ElusiveKey Problems in Managing Data
The volume of data within enterprises is exploding
Application silos make it difficult for people to collaborate
Users have little understanding of the quality of available data
Excessive time is spent on integration rather than innovation
IT is struggling to address rapidly changing business requirements
90% of upper level management feel they don’t have the necessary information for critical business
decisions; 50% of them are afraid they are making poor decisions because of it.”
― Economist Intelligence Unit
Poorly Managed Information Leads to Inefficiency and Risk
© SAP 2009 / Page 4
ComplianceFailures
Lower Profits
LowProductivity
50% to 70% of ERP implementations are reported as “challenged” in part to data integrity and/or data
accuracy problems.”
― Adaptive Growth, Inc.
90% of all businesses still do not have sufficient policies in place to meet data
governance regulations.”― IT Policy Compliance Group
“
“
“
Challenges to Effectively Managing InformationHow Does This Impact IT?
Top issuesHow do I empower all users with the information they need to make better decisions?
How do I help people to work across enterprise boundaries?
How do I provide applications with accurate data to drive business operations?
How do I implement data governance to ensure compliance and meet regulatory requirements?
How can I minimize cost and manage complexity?
Inconsistent Data Across Different SilosImpacts Business Results and Increases Costs
Data Managed in Silos
Finance Sales
Plant
Departments create and store their own data
Data inconsistencies, redundancies, and errors impact business results and increase costs
Manage Information as a Strategic AssetReduce Inefficiencies and Deliver Trusted Information
Enterprise Information Management
Finance Sales
Plant
Enterprise-Wide Reusable Information
Each information asset is readily understood, available and trusted
Formal information architecture to identify, share and govern all data
SAP Provides A Complete Approach To EIMEncompassing People, Process & Technology
Create Monitor
Enterprise Information Management
Executive Sponsor
Line of BusinessOwners
IT
Data Steward
Data Integration & Quality
Management
Master Data Management
Content & InformationLife-Cycle
Management
Data WarehouseManagement
PR
OC
ES
SP
EO
PLE
TE
CH
NO
LOG
Y
Cleanse Integrate Manage Govern Archive
SAP Provides Best-In-Class EIM SolutionsDeliver Information That Is Complete, Accurate, and Accessible
Data Integration & Quality Management:SAP BusinessObjects Data ServicesSAP BusinessObjects Data FederatorSAP BusinessObjects Text AnalysisSAP BusinessObjects Data InsightSAP Data Migration services
Master Data Management:SAP NetWeaver Master Data Management
SAP Master Data Governance for FinancialsSAP Data Maintenance by Vistex
Enterprise Data Warehousing:SAP NetWeaver Business Warehouse
SAP NetWeaver Business Warehouse AcceleratorSAP BusinessObjects Rapid Marts
SAP BusinessObjects Metadata Management
Content & Information Lifecycle Management:SAP NetWeaver Information Lifecycle ManagementSAP Extended ECM by Open TextSAP Document Access by Open TextSAP Archiving by Open Text
1. Why Enterprise Information Management2. Data Services: One tool for data integration and data quality
management3. Metadata Management: Impact and lineage to prove trustworthiness of
your data4. Some data services use cases in an SAP environment5. Wrap-up
Agenda
SAP BusinessObjects Data Services
One Runtime Architecture
One Development User Interface
One Metadata Repository
One Administration EnvironmentOne Set of Connectors
Data Services
Improve
Deliver
Transform
Access
Runtime Architecture
Metadata Repository
Development User Interface
Administration and Connectors
Runtime Architecture
Metadata Repository
Development User Interface
Administration and Connectors
Data Integrator XI R2
Data Quality XI R2
Data Services is the first single tool for data integration and data quality
SAP ERP, SAP CRM, SAP Master Data
Management (MDM), SAP NetWeaver BI, …
SOA
Shared MetadataImpact Analysis
Data Lineage
Dat
a pr
ofili
ng
Data Services Architecture
DataServicesEngine
Data Auditing
Data Validation
DataCleansing
RealTime
Batch
Files, XML,Mainframe, Excel, etc.
Oracle, SQL, DB2, etc.
PeopleSoft, Oracle Apps, Siebel, etc.
SAP R/3, SAP ERP,SAP NetWeaver BI
Query, Reporting,Analysis,
and Dashboards
Data Migration, Synchronization, …
SAP NetWeaver BI
OracleDB2Sybase & IQSQL ServerInformixTeradataODBCMySQLNetezzaHP NeoView
JD EdwardsOracle AppsPeopleSoftSiebelSalesforce.comSAP NetWeaver BISAP R/3
– ABAP– BAPI– IDoc
Text delimitedText fixed widthEBCDICXMLCobolExcelHTTPJMSSOAP(Web Services)
ADABASISAMVSAMEnscribeIMS/DBRMSBoth direct and change data
Enterprise-Wide Data Access
Broad connectivity to databases, applications, legacy, file formats, and unstructured data
Any text file type32 languages
Support for structured and unstructured data
Databases Applications Files/Transport Mainframe(with partner) Unstructured Data
Data Integrator : Enterprise-class Data Integration platform
Deliver trusted informationMarket leading data quality functionality within the data integration environmentBuilt-in features for validating data against business rules and auditing data movement executionEnd-to-end metadata impact analysis and lineage
Agility and ease-of-useSingle easy to use development interface to build, test,and deployWeb-based administration and management Collaboration features for team development
Deliver extreme ETL scalabilityParallelized processing down to the transform levelGrid computing for high availability and throughputServices-based architecture enabling right-time data deliveryPowerful prepackaged transformations
Explore, transform, and move data anywhere, at any frequency
Increase Value of Data Assets with Data Quality
Measure and analyze data through data assessment and continuous monitoring
Cleanse and enhancecustomer and operational data anywhere across the enterprise
Match and consolidatedata at multiple levels within a single pass for individuals, households, or corporations
Improve and automate the delivery of direct mail and goods
Data Cleansing examples : Customer Data (name)
Maggie.kline@future_electronics.com
Margaret Smith-Kline phd
FUTURE Electronics
5/23/03
101 6th ave
manhattan
ny
10012
001124367
Salutation: Ms.First name: MargaretLast name: Smith-KlinePostname: Ph. D.Match standards: Maggie, Peg, PeggyGender: Strong FemaleCompany name: Future ElectronicsAddress 1: 101 Avenue of the AmericasCity: New YorkState: NYZIP+4: 10013-1933Email: maggie.kline@future_electronics.comSSN: XXX-XX-XXXXDate May 23, 2003
Input record Output record
Data Cleansing examples : Product Data (Universal Data Cleanse)
Description
Kallkyle screw
test steel plate 20 x 35 mm
wire 23.33 x 40.50 cm
34 x 60 mm steel plate
steel plate 34,0 60 mm
34.0 x 60,0 mm steel plate
34 x 60 mm steel plate?
plate
steel plate
Input Parsed output
Product Dimension Type Form
screw Kallkyle
plate 20x35 mm steel test
wire 23.33 x 40.50 cm
plate 34 x 60 mm steel
plate 34 x 60 mm steel
plate 34 x 60 mm steel
plate 34 X 60 mm steel
plate
plate steel
Matching and Consolidation example
Ms. Margaret Smith-Kline Ph.D.
Future Electronics
101 Avenue of the Americas
New York NY 10013-1933
maggie.kline@future_electronics.com
May 23, 2003
Name: Ms. Margaret Smith-Kline Ph.D.
Company name: Future Electronics Co. LLC
SSN: 001-12-4367
Purchase date: 5/23/2003
Address: 101 Avenue of the Americas
New York, NY 10013-1933
Latitude: 40.722970
Longitude: -74.005035
Fed code: 36061
Phone: (222) 922-9922
Email: maggie.kline@future_electronics.com
Inpu
t rec
ords
Consolidated record
Maggie Smith
Future Electronics Co. LLC
101 6th Ave.
Manhattan, NY 10012
maggie.kline@future_electronics.com
001-12-4367
Ms. Peg Kline
Future Elect. Co.
101 6th Ave.
New York NY 10013
001-12-4367
(222) 922-9922
5/23/03
Data Services in action
Profile
Access
Cleanse Validate
Deliver
1. Our vision of information management2. Data Services: One tool for data integration and data quality
management3. Metadata Management: Impact and lineage to prove trustworthiness
of your data4. Some data services use cases in an SAP environment5. Wrap-up
Agenda
Data Lineage Helps Users Make Confident Decisions
Where did this number come from?
Data lineage provides information on how a number in your BI report is calculated during the ETL process and its origin
© SAP 2008 /
Data Lineage and Impact Analysis
Data Lineage: End users are able to trace back data in their reports to the original source through all different layers and transformation and presentation steps.
Impact Analysis: IT needs to know which reports and users will be affected when a change is made to one of the source systems.
Consolidate metadata from multiple systems
Integrate into one central, open metadata repository
Audit impact, usage, and lineage using the Metadata Explorer
Trust your metadata with added business content
Metadata Management Architecture
Custom Attributes Annotations, Metapedia
ConsolidateIntegrate
Audit
Business Metadata
1. Our vision of information management2. Data Services: One tool for data integration and data quality
management3. Metadata Management: Impact and lineage to prove trustworthiness of
your data4. Some data services use cases in an SAP environment5. Wrap-up
Agenda
Scenario 1: Data Quality for SAP CRM
Data Quality Management for SAP provides a prepackaged native integration of data quality best practices within the SAP environment using the BusinessObjects Data Services platform
Enforces data discipline directly within SAP CRM or SAP ERP systemsNo extracts for external processing required
Virtually undetectable presence that provides:Global address correction and standardization Comprehensive duplicate detectionConvenient record searching
Supported versionsSAP CRM: Releases 4.0 and 5.0 SAP ERP Central Component: Release 5.0 and 6.0SAP R/3 4.6C
Examples
Potential Duplicates Identified!
Review the Corrected and Fielded Information
Scenario 2: Load SAP NetWeaver BW
SAP NetWeaver 7.0 Business Warehouse
DataSource
InfoSource
PSA
Reporting Layer (Architected Data Marts)
Business Transformation Layer Operational
Data S
tore
Data Propagation Layer
Harmonization Layer
Corp. Mem-
ory
Data Acquisition Layer
Data Services
Order Management
Get easy access to data stored in non-SAP sources
Replace database connectivity with Rapid Mart application understanding
Include data cleansing and validation rules before loading data
Standardize, correct, and enhanceMatch and consolidateValidate against validation rules before loading into SAP NetWeaver BI
Scenario 3: Data Migration for SAP
Traditional Steps
SAPERP
LEGACYSYSTEM(S) ?
Provisionof data
“Let’s cross the fingersand hope it loads …
It is crucial to identify the right partner with the right expertise for your data migration project.
But attention:Data migration is far from easy.
Lack of experienceMigration project plan is unrealisticData quality issues/lack of confidence in the data You need to extend the consultants time for the SAP ERP project
Why?
More than 80% of data migration projects run over time and/or over budget. Cost overruns average 30%. Time overruns average 41%.Bloor, 2007
80% of organizations … will underestimate the costs related to the data acquisition tasks by an average of 50 percentGartner, Data Warehouse Infrastructure for Growth and Change
Analysts
Upload
SAP Data Migration ServicesEnd-to-End Solution for Data Migration
SAPERP
LEGACYSYSTEM(S)
SAPDATA MIGRATION
SERVICESFrameworkTemplatesMethodologyToolsExpertise
Data migration is a critical element in the success of the ERP implementation
Ensure accountability and a robust project approach to data migration from a single strategic vendor
Enable data governance best practices that live on after the projectIndustry-leading BusinessObjects Data Services platform benefits data migration and delivers many additional benefits in information management
Pre-built framework and tools reduce the need for custom scripts and deliver data insights more quickly and consistently
Engage business users early with better access to data quality and metricsThe right tools combined with the
right methodology and powerful expertise – That’s SAP Data
Migration Service
SAP Data Migration Framework Based on BusinessObjects Data Services
Data Governance Visualization
Project Management Summary MetricsTrack % quality and progress over time against projectmilestones
Business users/Data Steward reportsShow detailed data exceptions requiring resolution for each SAP Business Objects, e.g., Customer, including reconciliationexceptions
Migration Framework Staging
Cleanse, Harmonize, Reconcile
SAP Business Object Validation LibraryLibrary of DS objects to validate the data pre-load.The metrics created from this process drive the Data Governance Engine
XML, flat file
Oracle Apps, PeopleSoft, JDEdwards, Siebel
Legacy
Extract & transform to
SAP structures
SAP
SAP Load: XML, IDOC,
File
Post load reconciliation
BUSINESS
IT
Data Exceptions &
DQ Metrics
1. Our vision of information management2. Data Services: One tool for data integration and data quality
management3. Metadata Management: Impact and lineage to prove trustworthiness of
your data4. Some data services use cases in an SAP environment5. Wrap-up
Agenda
7 Key Points to Take Home
Data is spread throughout systems and applications in the enterpriseYou need a broad connectivity to all source systemsDon‘t forget the unstructured data!
Make sure you understand your data well before starting any projectProfiling your data will give you insight into your source data and identify potential data quality issues
The quality of data will vary among source systemsStandardize, cleanse, and enrich data before loading into the target applications
Avoid duplicate dataFind matches and consolidate to get one “golden record”
Use a “data quality firewall”Define validation rules to prevent incorrect data to get loaded
Deliver data in “right-time”Sometimes you need real-time services, in other cases you need to bulk load data overnight. One architecture should be able to serve all needs.
Don‘t underestimate the importance of metadataMetadata gives insight in where the data comes from and how it was transformed
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