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How to choose between the Inmon vs. Kimball approach for data warehouse design

Get an overview of Inmon v. Kimball approaches to data warehouse design and business intelligence and find a checklist to help you decide on an architecture approach.

What's your take on the Ralph Kimball vs. Bill Inmon approaches to data warehouse design?

Start by reading an overview of Inmon v. Kimball approaches to business intelligence.

Approach = architecture + methodology. There are two basic models for each. These are the first points to determine:

  • Define the bounds of your "enterprises"
  • Define the direction
  • Enterprise (Inmon) vs. data mart-oriented architecture (Kimball)
  • Enterprise (Inmon) vs. bottoms up-oriented methodology (Kimball)
  • Define federation characteristics

    Then, customize the approach by making decisions about each of the below points. As you can see, Inmon vs. Kimball plays an important, but incomplete part of any approach.

  • Build out scope
  • Business involvement
  • Definition of data marts – units of work or physical expansiveness of use of ETL tool in ETL processes
  • Data access options and manner of selection – by use, by enterprise, by category
  • Data retention and archival
  • Definition of data marts – units of work or physical
  • Expansiveness of use of ETL tool in ETL processes
  • Granularity of data capture
  • Integration strategy – virtual, physical
  • Metadata handling
  • Modeling technique(s)
  • Need, utility of and physical nature of data marts
  • Operational reporting and monitoring – real-time DW, EAI, BAM
  • Performance management
  • Persistence, need and physical nature of data staging
  • Physical instantiation of operational data stores – single-source, multi-source
  • Program development team engineering
  • Technology selection process – framework, best-of-breed
  • Source work effort distribution – source team, DW team, shared
  • Use of operational data stores for source systems – selective, complete

    As for deciding the architecture approach, I suggest the following:

    data architecture approach

This was last published in February 2009

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