1. Data Warehouse Prerequisites Familiarity with Microsoft SQL Server Familiarity with Microsoft SQL Server System Administration for Microsoft SQL Server 7.0 and Implementing a Database on Microsoft SQL Server 7.0 System Administration for Microsoft SQL Server 7.0 and Implementing a Database on Microsoft SQL Server 7.0 Knowledge of Transact-SQL Usage in Developing OLTP Systems Knowledge of Transact-SQL Usage in Developing OLTP Systems Basic Understanding of Programming Principles and Experience with a Scripting Language Basic Understanding of Programming Principles and Experience with a Scripting Language Understanding of Basic Database Design, Administration, and Implementation Concepts Understanding of Basic Database Design, Administration, and Implementation Concepts

2. What is Data Warehousing? Special Thanks to Bill Inmon, the “grandfather” of data warehousing. Peter Rawsthorne

3. OLTP vs. DSS Online Transaction Processing (OLTP) Online Transaction Processing (OLTP) Decision Support System (DSS) Decision Support System (DSS) OLTP OLTP –ATM, Bank Teller, Ticket Master, POS… DSS DSS –Marketing, What if?, Inventory, Health (Walmart)… –Click-through analysis

4. In-class Exercise 1. Break into teams of three 2. Think of a business or subject area 3. Determine three OLTP systems required to support business or subject 4. Determine two DSS systems required to support business or subject 5. Provide one example of how the DSS system could be used to predict the future

5. Exercise Example Business: Yacht Club Business: Yacht Club OLTP OLTP –Membership System –Accounting System –Yacht Racing Results System DSS DSS –Quarterly and Yearly Expenses –Race Results How much beer will we need for next years regatta for the male non-members who are crew on yachts over 40 feet? How much beer will we need for next years regatta for the male non-members who are crew on yachts over 40 feet?

6. What then is a data warehouse? A data warehouse is a: subject oriented, integrated, time variant, non volatile collection of data in support of management's decision making process.

7. Subject Orientation Data is organized via subject rather than process or business function. The application world is concerned both with data base design and process design. The data warehouse world focuses on data modeling and database design exclusively.

8. Integration Easily the most important aspect of the data warehouse environment is that data found within the data warehouse is integrated. ALWAYS. WITH NO EXCEPTIONS. consistent naming conventions, consistent measurement of variables, consistent encoding structures, consistent physical attributes of data, and so forth.

9. Time Variant OPERATIONAL Current valued data Current valued data Time horizon: 60 – 90 days Time horizon: 60 – 90 days Key fields may or may not have an element of time Key fields may or may not have an element of time Data can be updated Data can be updated DATA WAREHOUSE Snapshot data Time horizon: 5 – 10 days Keys do not have an element of time Once snapshot is made, records cannot be updated

10. non volatile Inserts, deletes, and changes - are done regularly to the operational environment on a record by record basis. There are only two kinds of operations that occur in the data warehouse - the initial loading of data, and the access of data.

11. The structure of the warehouse The different components of the data warehouse are: metadata, current detail data, old detail data, lightly summarized data, and highly summarized data.

12. Current Detail Data Most recent happenings Most recent happenings Voluminous Voluminous Lowest level of granularity Lowest level of granularity Almost always stored on disk storage Almost always stored on disk storage Fast to access Fast to access Expensive and complex to manage Expensive and complex to manage

13. Older detail data Stored on some form of mass storage Stored on some form of mass storage Infrequently accessed Infrequently accessed Stored at a level of detail consistent with current detailed data Stored at a level of detail consistent with current detailed data Often stored on an alternate storage medium Often stored on an alternate storage medium Anticipated large volume Anticipated large volume

14. Lightly summarized data Distilled from the low level of detail Distilled from the low level of detail Almost always stored on disk Almost always stored on disk Design issues facing the data architect are; Design issues facing the data architect are; –what unit of time –what contents – attributes Frequently mined data, a lot of “what if?” Frequently mined data, a lot of “what if?”

15. Highly summarized data Compact and easily accessible Compact and easily accessible Sometimes found in the data warehouse Sometimes found in the data warehouse Sometimes found outside the data warehouse Sometimes found outside the data warehouse In any case, the highly summarized data is part of the data warehouse In any case, the highly summarized data is part of the data warehouse Yearly or multi year summaries Yearly or multi year summaries

16. Metadata Sits in a different dimension Sits in a different dimension Contains no data directly taken from the operational environment Contains no data directly taken from the operational environment Special and very important role Special and very important role Metadata is used as: Metadata is used as: –a directory to locate the contents –a guide to the mapping of data –a guide to the algorithms used for summarization

17. Metadata – levels of summarization

18. Flow of Data data enters from the operational environment, it is transformed data goes into the current detail level of detail It resides there and is used there until one of three events occurs: –it is purged, –it is summarized, and/or –it is archived.

19. Using the Data Warehouse

20. Example

21. Summary A data warehouse is a A data warehouse is a subject oriented, integrated, time variant, non volatile collection of data in support of management's decision needs. Four levels of data warehouse data: Four levels of data warehouse data: old detail, current detail, lightly summarized data, and highly summarized data. Metadata is a very important part Metadata is a very important part

22. Lab deliverables W2KS Install W2KS Install SQL7.0 Install SQL7.0 Install SQL7.0 OLAP Services Install SQL7.0 OLAP Services Install MSPress install MSPress install Complete MSPress Chapter 1 Complete MSPress Chapter 1

23. Contact Information Peter Rawsthorne, B.Tech, MCSD, MCT, CCR President, Eclectic Endeavours Inc. 559A Artisan Lane PO Box 281 Bowen Island, BC CANADA V0N 1G0 Phone: 604-947-2760 Fax: 604-947-2715 email: peterr@endeavours.com web: http://www.endeavours.com