Introduction to Business Intelligence

What is Business

Intelligence ?

What is Business Intelligence?

“BI results when organizational , business and are designed and implemented with the goal of the strategic and operational capabilities of a wide range of internal and external .”

- International Data Corporation (IDC)

culture processes technologies

improving decision-making

stakeholders

What is Business Intelligence?

Culture, processes and technologies to improve decision making for stakeholders.

Business Intelligence history

In 1989, Howard Dresner proposed "business intelligence" as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."

Related data disciplines

• data mining• statistical analysis• forecasting• decision support

BI is used everywhere

FACTS: DATA→INFORMATION→KNOWLEDGE Facts are just actual or hypothetical representations. Data is the individual raw facts that are

out of context, have no meaning, and are difficult to understand

in context, have meaning and can be readily understood.

Information is a set of data in context that is relevant to one or more entities at a point in time or for a period of time.

Knowledge is the fact or condition of knowing something with familiarity gained through experience or association.

OLTP vs. OLAP

OnLine Transaction Processing (OLTP) systems are used for handling transactional data and optimized for performance during Read/Write operations specifically for a faster response (Relational Modeling).

Online Analytical Processing (OLAP) systems are read-only and are specifically meant for analytical purposes (Dimensional Modeling).

Small OLTP database

Business Issue: A customer’s order was seriously delayed.

Manager: Why?Order Fulfillment: Supplier issue.

Simple Business Question:Who was our product supplier?

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23

4

Small OLTP database

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23

4

5

6

7

8

9

1011

1228

33

42 89

Large OLTP database

The Data Warehouse

A data warehouse is a for all or parts of the that an 's various business systems

- Bill Inmon

central repository significantdata enterprise

collect

The Data Warehouse

Central repository for all significant data that an enterprise collects.

Extract, Transform and Load (ETL)

ETL tools perform three functions to move data from one place to another:

Extract data from sources such as ERP or CRM applications;

Transform that data into a common format that fits with other data in the warehouse; and,

Load the data into the data warehouse for analysis.

Ralph Kimball Bill Inmon

Star Schema Snowflake Schema

Vs.

Data Warehouse: Data Model

Data Model: Star Schema

1 to Many

Data Model: Snowflake Schema

1 to Many to Many

The OLAP Cube

Data Warehouse: Fact & Dimensions

Fact Measure

• What the business does Business Process

• Usually describes an action or event (verb)

Fact Tables: contain measure columns and dimension key columns

Measure: numerical values that can be aggregatedDimension: group of attributes that describe a business process

Attribute: characteristics of a dimension member

• Fact Internet Sales• Sales Amount• Discount Amount• Profit• Profit Margin

• Dim Customer• Name• Gender• Yearly Income

• Dim Product• Color• Size

Data Warehouse: Relationships

Business Process: Sales

DimCustomers

DimTime

DimProducts

FactOrders

FactOrdersKeyDimProductsKeyDimCustomersKeyDimTimeKeyMeasure QuantityMeasure PriceMeasure Discount

Fact:37 Lemons were sold during April in our Chicago stores.

Measure: Units sold

Dim

en

sio

n:

Pro

duct

Dimension: Time

Dim

ensi

on: G

eogr

aphy

Members, Leaf and Nonleaf Cells (aggregation)

Calculated by MDX

Dimension

Dimension

Dimension

Members

Data warehouse and data marts

Typical Business Intelligence Lifecycle

Layers of Business Intelligence

Business Intelligence In Microsoft

Presentation• SQL Server Reporting Services• SharePoint • Performance Point• Excel

Analysis• SQL Server Analysis Services• PowerPivot

E.T.L• SQL Server Integration Services• Excel

BI Layers at Microsoft

BI Microsoft Tools

SQL Server Data Tools

Microsoft SQL Server Analysis Services (SSAS)

Delivers business intelligence applications with: OLAP (Unified Dimensional Model (UDM))

Data mining.

Design, create, and manage multidimensional structures that contain data aggregated from other data sources, such as relational databases.

Unified Dimensional Model (UDM) provides a bridge between the

user and the data sources

The user issues queries against the UDM using a variety of client tools, such as Microsoft Excel.

Benefits: Greatly enriches the user model.

Provides high performance queries supporting interactive analysis, even over large data volumes.

Captures business rules in the model to support richer analysis.

Supports ‘closing the loop’: letting users can act upon the data they see. 

Accessing the Data Sources Directly

SELECT Quotas.QuotaAmount, Quotas.EmployeeId, …

FROM OPENROWSET('SQLOLEDB','seattle1'; 'Sales'; 'MyPass',

'SELECT * FROM Forecasts.dbo.SalesQuota’ ) As Quotas

SELECT Sales.SalesAmount, Sales.EmployeeId, …

FROM OPENROWSET('SQLOLEDB','seattle2'; ‘Orders'; 'MyPass2',

'SELECT * FROM Sales.dbo.EmpSales’ ) As Sales

HR

Sales

Accessing the Data Sources by UDM

UDM contentsQuery

Sales Amount and Quota by Product Category

Multidimensional Expressions (MDX)

Query language used to work with and retrieve multidimensional data in (SSAS)

Based on the XML for Analysis (XMLA) specification

Used for:

Return data to a client application from a SSAS cube.

Format query results.

Perform cube design tasks, including the definition of calculated members, named sets, scoped assignments, and key performance indicators (KPIs).

Perform administrative tasks, including dimension and cell security.

MDX Sample

SELECT

{ [Measures].[Sales Amount],

[Measures].[Tax Amount] } ON COLUMNS,

{ [Date].[Fiscal].[Fiscal Year].&[2006],

[Date].[Fiscal].[Fiscal Year].&[2007] } ON ROWS

FROM [Adventure Works]

WHERE ( [Sales Territory].[Southwest] )

Thank you