Introduction to Enterprise Data Warehouse (EDW).

1. Presented by: Jonathan Bloom
Senior BI Consultant, Agile Bay, Inc.

2. Customers & Partners
Jonathan Bloom
Current Position:
Senior BI Consultant
Blog:
http://www.BloomConsultingBI.com
Twitter:
@SQLJon
Linked-in: http://www.linkedin.com/BloomConsultintBI
Email:
JBloom@agilebay.com

3. w w w . a g i l e b a y. c o m

4. Agenda
 Why EDW
 Flow of Data
 Pros and Cons
 Q&A

5. Why EDW?

6. Convert Data to Information
 Accumulating Data
 Manage the Business
 OLTP != Reporting
 Apply Business Rules
 Clean Data
 Analytics
 Distribution

7. EDW Role








Reporting Lifecycle
Domain Knowledge
Interact with Business
Gather Specs
Estimate Time
Knowledge of Database
SQL Skills
Change Management

8. Requirements
 Access to Database
 Valid Credentials
 Location of Tables
 Business Intelligence Dev Studio (BIDS) 2008 R2
 SQL Server Data Tools 2012
 SQL Analysis Cubes

9. EDW Architecture
 Source System
 Staging
 Raw
 Master Data Services
 Enterprise Data Warehouse
 Analysis Services Cubes

10. Data Modeling
 Kimball Methodology
 Star Schema

Pattern forms a graphical “Star”
 Snow Flake Schema

Branches

11. Tables
 Dimension Tables
 Describe Data
 Fact Tables
 Measures (Sums, Counts, Max, Min, etc.)
 Contain Surrogate Keys

Link back to Dim Tables

12. SK Keys
 Surrogate Keys
 Substitution for the natural primary key
 Unique Identifier
 Auto Integer, Indexed, Primary
 Foreign Key in other tables

13. AK Keys
 Alternate Keys
 Unique Identifier from Source System
 Typically Varchar

14. Staging
 Create Tables
 Dim Tables
 Fact Tables
 Use SQL Statements
 Pull Data
 Truncate and Reload
 SSIS = ETL

15. DW
 Create Tables
 Dim Tables

SK / AK
 Fact Tables

SK
 Use SQL Statements
 Pull Data
 SSIS = ETL
 Time Stamps

16. Slowly Changing Dimensions
 Type 0 method is passive
 Values remain as they were at the time the dimension
record was first inserted
 Type 1
 Overwrites old with new data
 Does not track historical data
 Type 2
 Tracks historical data by creating multiple records

17. Null Values
 -1 Row
 Null Vales in Fact Tables = -1

18. Date Dimensions
 Create Scripts
 Fiscal Year
 Custom Start / End Dates
 Key Example: 20140226

19. Date Dimensions

20. Dim Tables

21. Dim Table Example

22. Fact Tables

23. Fact Table Example

24. Fact Table Keys

25. Fact Table Keys

26. Analysis Server

27. Cubes (Measure Groups)

28. Cubes (Dimensions)

29. SSAS Cubes

30. SSAS
 Create Connections
 Add Data Sources
 Create Relationships
 Add Dimensions
 Create Measure Groups / Measures
 Create Calculated Measures
 Create Hierarchy’s

31. Visual Studio

32. Create SSRS Report with SSAS Cube

33. SSRS SSAS (MDX) Demo:
 Open SDT
 Connect to Cube
 Select Measures
 Add Fields to Report
 Run Report
 Deploy Report

34. SSRS SSAS (MDX) Demo:

35. SSRS SSAS (MDX) Demo:

36. Connect to SSAS Cube via Excel

37. Excel – Cube Demo:
 Open Excel
 Create Connect

38. Excel – Cube Demo:

39. Excel – Cube Demo:

40. Excel – Cube Demo:

42. Summary
 Learn EDW
 Data Modeling
 ETL – SSIS
 Cubes – SSAS
 Reports – SSRS / Excel Pivot Tables
 Stay Current
 Never stop learning!

43. Blog:
http://www.BloomConsultingBI.com
Twitter:
@SQLJon
Linked-in: http://www.linkedin.com/BloomConsultingBI
Email:
JBloom@agilebay.com