1. ISAS - Strategic Business Systems Group Data Warehouses and Business Information Quality John Shelton Strategic Business Systems Group Manager

2. Presentation Objectives Roles of the operational databases vs data warehouse within the organisation Low quality MIS vs high quality MIS ETL processing Quality data vs quality information Steps to implement a data warehouse MIS software demonstration

3. Operational Reporting Live Student Records Live Finance Records Live HR/PR Records Operational Reports Operational Reports Operational Reports

4. Drawbacks of Operational Reports Reports often have to be against current / live data sets i.e. immediate and up to date Performance implications due to : –Database Design being transaction based –Impact on Live System i.e. clashes with users activity during the day Result of above = overnight reporting

5. DMU MIS Requirements Information needed to make informed business decisions Acceptable response times Ability to Report over multiple time periods Drill down analysis Flexible reporting parameters To present information so that it can be understood and easily assimilated

6. Current - Low Quality MIS Information Local Data Create Retrieve Not Again! Local Data Local Data George Jim

7. Low quality information results in : Badly informed decisions and often resulting in unrecoverable damage staff performing work over and over again unnecessary time to investigate the integrity of the data before it can be used reformatting of data before it can be used miscommunication within the business missing business opportunities

8. Need - High Quality Information Trusted Data Warehouse WOW ! Create once Retrieve once George Jim

9. Data Warehouse benefits Off-line reports not impacting live systems Can pull data from many sources to add value Data structured for fast reporting not transaction processing i.e. de-normalised Allows pre-processing of data Summarised data over multiple time periods Reliable and trusted information

10. The MIS data warehouse (Live) QL Students (Live) QL Finance (Operational / Transaction based Databases) ETL Processing MIS Reports (Off-line) Data Warehouse (Pre-processed snap-shot data) External Data source

11. Data Warehousing Success Factors The success of a data warehouse is dependent on collecting, managing, and dis- seminating quality management information that supports the strategic and tactical business processes. Without quality information, the data warehouse will fail

12. What is Quality ? (exercise)

13. What is Quality ? “Consistently meeting customer’s expectations” Improving the things customers care about and that make their lives easier and more worthwhile

14. What is Information ? Is this Quality Data ? How do I know ? 59CICD504 Because it matches the specified Data Definition of : D2 +A1 +A3 +D3 59 C ICD 504

15. What is Information ? When does it become Information ? When it is meaningfully presented (59CICD504) Department code59 (ISAS) Capital or RevenueC (Capital) Project CodeICD (WebFocus) Expense code504 (Consultancy)

16. Information can be represented as Information = (Data + Definition + Presentation)

17. Information Quality is : “The right data, with the right completeness, in the right context, with the right accuracy, in the right format, at the right time, at the right place, for the right purpose”

18. Information Quality The Right data Right Completeness Right Context Right Accuracy Right Format Right Time Right Place Right Purpose The data I need All the data I need Data I understand Data I can trust I can use it easily When I need it Where I need it To meet my objectives

19. How to deliver the Data warehouse Project Sponsor Getting the right people with the right knowledge to develop a specification Agreeing business definitions (exercise !) Agreeing and owning and signing off the specification Producing the Technical design Development of ETL process and reports

20. How to deliver the data warehouse Performance of the software Pilot the system before live production Have ‘champions’ within the user base Provide user training Provide clear and precise user documentation Provide on-going development and support

21. FACT If the data warehouse does not deliver reliable information that supports the customers decisions and strategic processes to their satisfaction, then history will repeat itself

22. Quality quotations : “People forget how fast you did a job - but they remember how well you did it” - Howard Newton “One accurate measurement is worth a 100 expert opinions”- US Admiral

23. Recap / summary Roles of the operational databases vs data warehouse within the organisation Low quality MIS vs high quality MIS Value added by ETL processing Quality data vs quality information Importance of clarity of definitions Steps to implement a data warehouse

24. MIS Demonstration