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Akinwale O. Falodun CMSN 601 Spring 2001

Data Warehouse and Data Marts. Akinwale O. Falodun CMSN 601 Spring 2001. Terms to remember. DW = Data Warehouse DM = Data mart Bill = William. 3. Agenda. Define Data Warehouse and Data Mart Characteristics of DW and DM Contrast DW and DM DW, DM Architecture

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Akinwale O. Falodun CMSN 601 Spring 2001

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  1. Data Warehouse and Data Marts Akinwale O. Falodun CMSN 601 Spring 2001

  2. Terms to remember • DW = Data Warehouse • DM = Data mart • Bill = William Presenter: Akinwale O. Falodun 3

  3. Agenda • Define Data Warehouse and Data Mart • Characteristics of DW and DM • Contrast DW and DM • DW, DM Architecture • Why does a company need a DW • Why does a company need a DM • The debate - Ralph Kimball and William Inmon • Problems with DW and DM • Future of DW and DM • Conclusion Presenter: Akinwale O. Falodun 3

  4. What is Data warehouse? • According to Bill Inmon, who is often called [The Father of Data Warehousing], “data warehouse is a subject oriented, integrated, time variant, non-volatile collection of data that supports the decision-making capabilities of the business user.” • Oracle Corporation defines data warehouse as a “strategic collection of all types of data in support of the decision-making process at all levels of an enterprise.” • Important Definition Elements • Subject Oriented, Integrated,Time Variant • Non volatile collection of data, Decision-making capabilities* Presenter: Akinwale O. Falodun 4

  5. Characteristics of DW • Central Repository • Subject Oriented • Integrated • Time Variant • Non volatile collection of data • Viewing a Snapshot • Consistent Data • Decision-making capabilities* Presenter: Akinwale O. Falodun 6

  6. What is Data Mart? • A data mart is an implementation of data partitioning strategy that enables targeted users to access functionally departmentalized data. A data mart is a subset of a data warehouse. • It is also known as a business area warehouse or a departmental warehouse. • Important Definition Element • Data partitioning • Targeted users • Functionally departmentalized data • Subset of a DW Presenter: Akinwale O. Falodun 5

  7. Two Types of Data Mart? • Dependent DM = Fed by DW • Independent DM = Not fed by DW Presenter: Akinwale O. Falodun 5

  8. Characteristics of DM • Departmental Repository • Departmentally Subject Oriented • Time Variant • Non volatile collection of data • Consistent Data • Decision-making capabilities Presenter: Akinwale O. Falodun 6

  9. Critical Success Factor • Clearly define scope of DW or DM • Scope must not be changed during development • Flexible design to accommodate future changes • Identify Sponsors and Users • Gain support for Requirements, Analysis, Prototyping and Testing • Strategies should include Prototyping and Piloting • Implementation and Deployment - one stage at a time • Implementation stages should be meaningful and logical • Software used should meet today’s needs plus future Presenter: Akinwale O. Falodun 6

  10. Hardware & Software requirement • Warning! - Please Address this at the early stage • Server Products: • Express Server • Web Server • Processing and Modeling tools: • SQL*Loader • Gateways • Queries and analysis: • Discoverer • Express Analyzer Presenter: Akinwale O. Falodun 6

  11. A Typical Data Warehouse Architecture Presenter: Akinwale O. Falodun 6

  12. A Complex Data Warehouse Architecture Presenter: Akinwale O. Falodun 6

  13. Contrasting DW and DM Presenter: Akinwale O. Falodun

  14. KIMBALL Collection of DM = DW DM grows big enough = DW Dimensional modeling Build what the users need INMON DM extracted from DW DM growth = big DM DM lacks thorough architecture DM not scalable DM lacks integration William Inmon Vs Ralph Kimball “The data warehouse is nothing more than the union of all the data marts” - Ralph Kimball “Data Mart Does Not Equal Data Warehouse” - William Inmon Presenter: Akinwale O. Falodun

  15. Benefits of DW • Competitive advantages • Quick reaction to changes • Adapting to changing customer needs • access to data in different formats • Rapid payback on investment within a short period of time • Powerful strategic decision making tool • Stable data, Subject Oriented • Short term goal attainment, Long term goal assurance • Hardware used is cost effective, robust • Information management system Presenter: Akinwale O. Falodun

  16. Benefits of DM In addition sharing some of the DW benefits... • Departmental data • Ease of access • Ease of navigation • Reduces Traffic into DW Presenter: Akinwale O. Falodun

  17. Problems facing DW • Overall Cost • Expensive Hardware • Expensive Sophisticated Software • Expensive Skilled Team • Training cost • Time Consuming Presenter: Akinwale O. Falodun

  18. Problems facing DM - Independent DM • Redundant Data • Redundant Processing • Lack of Scalability • Non-Integrated Presenter: Akinwale O. Falodun

  19. Future of DW and DM Presenter: Akinwale O. Falodun

  20. Conclusion • “You can catch all the minnows in the ocean and stack them together and still do not make a whale.”Bill Inmon, January 8, 1998. Presenter: Akinwale O. Falodun 7

  21. End of presentation For informative articles, visit: http://www.datawarehouse.com/iknowledge/articles QUESTION ? Presenter: Akinwale O. Falodun

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