1. The Death of the Data Warehouse Michigan Oracle User Summit 14 November 2012

2. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M The Business Problems We’re Trying to Solve w/ DW & BI? Business people can’t get to their data Running summary reports out of transaction databases is very slow Performance issues of transaction DB Reporting is complex Disparate databases - No integrated view of the whole company Transaction systems discard history

3. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M What we need to solve these Subject Oriented Integrated Time variant Non volatile

4. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M What we create

5. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M The Traditional DW Model Complexities – Technologies to master Data modeling ETL BI DBA – Workplan steps to complete Design data mart databases Design DW databases Design BI tool metadata Build flows from source systems to DW Build flows from DW to data marts Build BI metadata Result – Time consuming – Brittle (e.g. change to one column in the source ripples through architecture)

6. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Traditional BI Development $ Success?Success?

7. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Data Warehouse Definition – The Physical DB Implications Subject Oriented Integrated Time variant Non volatile This is a LOGICAL definition, not a physical one – it says nothing about how the data must be stored or accessed

8. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M New Generation of BI Tools (QlikView, Tableau, etc.) They contain their own, non-relational, self-managing data stores. They can import data from multiple sources into a single, accessible data store. They join related data together, like a relational database. They provide predictable, blisteringly fast query performance They provide very easy, user-friendly user interfaces. They can contain, and rapidly summarize, atomic-level, granular data. They can be incrementally refreshed, enabling the storage of history. These tools meet the definition of a data warehouse but are far more efficient

9. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M The Traditional DW Model TRADITIONAL Complexities – Technologies to master Data modeling ETL BI DBA – Workplan steps to complete Design data mart databases Design DW databases Design BI tool metadata Build flows from source systems to DW Build flows from DW to data marts Build BI metadata Result – Time consuming – Brittle (e.g. change to one column in the source ripples through architecture) NEW WORLD Complexities – Technologies to master In memory tool – Workplan steps to complete Build flows from source systems to DW Build reports Result – Agile – Easily revised

10. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Preferred Model of BI Development $ User Input Dev & Rvw Quit No User Input Dev & Rvw Yes Quit No User Input Dev & Rvw Yes Develop DW in Parallel with Input from BI (If Necessary)

11. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M In Memory Advantages & Disadvantages Replace DW Isolate operational systems from query demands Improve query response times with data structures optimized for query Provide a place to store history that might otherwise be lost Provide a place where users can access data integrated from multiple systems Users prefer the in-memory / visualization approach Less administration vs. traditional BI Rapid development / rapid prototyping / incremental delivery Data set sizeReal time / Operational reportingNo access from other tools Great for visualization & analysis - not for ‘greenbar’ replacement Data cleansing & complex integration MDM

12. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Questions?

13. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M

14. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M

15. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Traditional BI Architecture (e.g. Cognos Rpt Studio) Point & click to generate SQL Database – Operational or Informational Format presentation Source DB 1 Source DB 2

16. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M QlikView Architecture Point & click to generate Query Format presentation Source DB 1 Data Warehouse Associative DB

17. ©2004 Dataspace Incorporated. Any unauthorized use of these materials violates copyright and trademark laws. W W W. D A T A S P A C E. C O M Demo