1. Dimensional Modeling (2) Gregory Ng Data Warehouse / Business Intelligence Designer 17th March 2008

3. Dimension Model vs. ER Model (cont…) Dimension Model: Denormalized to 2NF (reduce number of tables and join paths), creates redundancy 1 major type of relationship, one-to-many Ideal for SELECT operation Top down approach: focus on business process Designed to support analytical queries and user access Handle anomaly within ETL Predictable SQL Perfect for OLAP applications

4. Case Study 1 Project Writeaway (2009) Database SQL Server 2000 Reporting Hyperion IR Star Schema 4 No. of records ~ 1 mil Load Complete refresh Typical report generation time ~3 seconds Project build time 4 months Highlights Drill Across Factless Fact Table Dimension Outrigger Dimension Bridging Junk Dimension

5. Case Study 2 Project Absenteeism (2006) Database SQL Server 2000 Reporting Cognos Star Schema 1 No. of records ~ 1 mil Load Incremental Typical report generation time ~25 seconds Project build time 4 weeks Highlights Drill Across Slowly Changing Dimension Active Data Warehouse

6. Case Study 3 Project Mortgage Wealth DNA (2009) Database Teradata Reporting Hyperion IR Star Schema 3 No. of records ~ 150 mil Load Incremental Typical report generation time ~20-30 seconds Project build time 3 months Highlights Drill Across Aggregate Join Index Partitioning/Multi-Partitioning 99% aggregation done on Teradata on the fly – minimise data retrieval

7. Case Study 4 Project Commway (2005) Database SQL Server 2000 Reporting Cognos Star Schema 3 No. of records ~ 10 mil Load Incremental Typical report generation time ~ 30 seconds Project build time 18 months Highlights Drill Across Slowly Changing Dimension Active Data Warehouse .NET Front End for Data Entry (4000+ Users)

10. Shared Dimension (Conformed) and Drill Across Drill across to different business process fact can be enable via confromed dimension

11. Shared Dimension (Conformed) and Drill Across (cont…) To produce the following drill across report: SELECT Customer, Actual Amount, Forecast Amount FROM --Subquery “Act” returns Actuals ( SELECT Customer, SUM(Sales Amount) AS Actual Amount FROM Sales Fact, Customer JOIN …) Act INNER JOIN --Subquery “Fsct returns Forecast ( SELECT Customer, SUM(Forecast Amount) AS Forecast Amount FROM Forecast Fact, Customer JOIN …)Fsct --Join for the above 2 result sets ON Act.Customer = Fcst.Customer AND … Back Customer Actual Amount Forecast Amount Bill Owen $76859 $75768 James Brown $63548 $85676

13. Accumulating Snapshot Schema Useful to track a multi-step business process – capture the process history in a single row Design to ease the query design and query performance Back

17. Bus Matrix Back

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