Data Warehouse to BI
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Agenda
 Review
 Preparing the DW for Analysis
 Microsoft BI Platform Overview
 Building a Cube in SSAS
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DW Development Approach: Kimball
 Methodology
 DW Project Lifecycle
 Business requirements
 Business Requirements Documentation
 Bus Matrix
 Design, build and deliver in increments
 DW Architecture
 DW Design
 ETL system
 Cube, Reports, query tools, …
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Data Warehouse Project Lifecycle
Source: Mundy, Thornthwaite, and Kimball (2006). The Microsoft Data Warehouse Toolkit, Wiley Publishing
Inc., Indianapolis, IN.
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DW Development Approach: Kimball
 Methodology
 DW Project Lifecycle
 Business requirements
 Business Requirements Documentation
 Bus Matrix
 Design, build and deliver in increments
 DW Architecture
 DW Design
 ETL system
 Cube, Reports, query tools, …
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BI Application Specification,
Development
 Specification
 Standard Reports
 Layout-led discovery
 Enrollments by course and timeframe
 Average GPA by course and timeframe
 Analytic Applications
 Data and Model-led discovery
 Year-to-year changes in average GPAs by college
 Students most likely to have good overall GPAs
 Development
 (SSAS, Excel) Multidimensional Cube, Data-led discovery
 (SSRS, Excel) Standard Reports
 (SSAS, Excel) Mining Model-led discovery
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Displaying the Cube
 Cube browser—resembles spreadsheet
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Displaying the Cube, cont…
 Pivot table - a multidimensional spreadsheet
OLAP Models
Model
Description
Comparison
MOLAP
Data and aggregates in
multidimensional database
Best query performance;
proprietary
ROLAP
Data and aggregates stored in
relational database
Worst query performance;
leverage existing infrastructure
HOLAP
Hybrid approach; detail data stored
in relational database, aggregates
stored in multidimensional
database
Best processing performance;
query performance better than
ROLAP, not as good as MOLAP
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Microsoft BI Platform
RDL
MDX, DMX
SQL
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Microsoft BI Platform: Development
Interfaces
 SQL Server Database Engine
 Interface: SSMS
 SQL Server Integration Services
 Interface: SSDT
 SQL Server Analysis Services
 Interface: SSDT
 SQL Server Reporting Services
 Interface: SSDT
 MS Office Excel Data Mining Add-In
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Preparing the Data Warehouse for
Analysis
 Build a multidimensional cube
 Refine
 Create KPIs…
 Design reports
 Design mining models
 Deploy cube, reports, models to the server
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Building an Analysis Services Cube
 Create:
o Data Source
o Data Source View
o Cube
 Deploy/Process Cube
 Use the Cube
 OLAP Analysis
o Reports
o Data Mining Models
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Example
http://www.accelebrate.com/sql_training/ssas_
2008_tutorial.htm
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