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James Serra's Blog

James is currently a Senior Business Intelligence Architect/Developer and has over 20 years of IT experience. James started his career as a software developer, then became a DBA 12 years ago, and for the last five years he has been working extensively with Business Intelligence using the SQL Server BI stack (SSAS, SSRS, and SSIS). James has been at times a permanent employee, consultant, contractor, and owner of his own business. All these experiences along with continuous learning has helped James to develop many successful data warehouse and BI projects. James has earned the MCITP Business Developer 2008, MCITP Database Administrator 2008, and MCITP Database Developer 2008, and has a Bachelor of Science degree in Computer Engineering. His blog is at .

Does Business Intelligence equal Data Warehousing?

I have seen many times at clients where the terms business intelligence and data warehousing are used interchangeably.  In reality, these are two separate disciplines. This is especially true for enterprise data warehouses due to an EDW’s scope, complexity, and large volumes of data.

As seen in the data warehouse maturity model (a future blog post), as a data warehouse matures, the data warehouse team spends more and more resources on data integration.  This shifts the focus from data consumption to data production.

Simply put, data warehousing and BI differ because:

  • The primary focus for a data warehouse is the production of data
  • The primary focus for BI is the consumption, presentation, and delivery of the data produced by the data warehouse

One example of where BI is confused with data warehousing within the SQL Server community is the
AdventureWorks samples available at the Microsoft SQL Server Community Projects & Samples site.
These samples include the following databases:

  • A sample OLTP database (AdventureWorks2012)
  • A sample data warehouse database (AdventureWorksDW2012)
  • A sample SQL Server Analysis Services (SSAS) database, or cube (multidimensional and tabular)

The AdventureWorks sample data warehouse link provides more information about the AdventureWorks data warehouse and supporting scenarios in which data warehouse, data mining, and Online Analytical Processing (OLAP) are relevant.  However, note that these are BI scenarios because the focus is on consumption, not production.  There are no samples for the data warehouse production scenario; instead, the data warehouse is populated directly from Comma Separated Values (CSV) files.  So these AdventureWorks samples should be thought of as business intelligence samples, not data warehouse samples.

In summary, BI focuses more on data consumption and should not be equated to data warehousing, which concentrates more and more on data production as it matures, especially when you are working with very large data volumes.

More info:

Microsoft EDW Architecture, Guidance and Deployment Best Practices – Chapter 2: Data Architecture


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