BeyeSearch - Focused Search. Quality Results for Business Intelligence, Business Performance Management and Data Warehousing

1. Kimball Group and Kimball University

A definitive source for quality dimensional data warehouse consulting and education. The group is focused on developing, teaching and applying dimensional data warehouse design techniques for IT business intelligence professionals through consulting, writing and education.
http://www.rkimball.com
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2. Data Warehouse Architecture Articles from Ralph Kimball
Data Warehouse training articles from Ralph Kimball. Ralph Kimball is known worldwide as an innovator, writer, educator, speaker and consultant in the field of data warehousing. To date Ralph has written more than 100 articles and columns on the subject.
http://www.rkimball.com/html/articlesArchitecture.html
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3. A Practical Method for Building a Data Warehouse
A matrix depiction of the data warehouse plan is a pretty good planning tool once you have gathered the business requirements and performed a full data audit. This matrix approach has been exceptionally effective for distributed data warehouses without a center.
http://www.intelligententerprise.com/db_area/archives/1999/990712/webhouse.jhtml?_requestid=126837
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4. Ten Mistakes to Avoid in Bottom-up Development
There is a vigorous debate going on in the DW community about whether to build applications top-down or bottom up. Adherents of the top-down approach recommend utilization of the Corporate Information Factory (CIF) architecture.
http://www.mimno.com/articles/article9.html
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5. Conform facts and dimensions to evolve your data warehouse over time
Building an enterprise data warehouse can be a complex and risky undertaking. Some organizations prefer to build smaller data marts first and let their data warehouse evolve over time. We'll tell you how planning can ensure the success of this approach.
http://techrepublic.com.com/5100-6301-1031680.html
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6. Data Warehouse Designer: Divide and Conquer
But, more likely, when the enterprise decides to create a set of common labels across all the sources of data, then the separate data mart teams (or, equivalently, a single centralized team) must sit down to create master dimensions that everyone will use for every data source.
http://www.intelligententerprise.com/021030/517warehouse1_2.jhtml
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7. Is The Future Of Data Warehousing
Last week I put together a posting on new developments in Oracle data warehousing, where I mentioned that much of Oracle's marketing focus in this area is centred around real-time business intelligence.
http://www.rittman.net/archives/000867.html
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The Bus Architecture