Rating Your Dimensional Data Warehouse
Intelligent Enterprise Magazine article by Ralph Kimball that explains the first 12 of twenty criteria for comparing data webhouses.
http://www.intelligententerprise.com/000428/webhouse.shtml
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Is Your Dimensional Data Warehouse Expressive?
Intelligent Enterprise Magazine article by Ralph Kimball completes the 20 criteria for rating your dimensional data warehouse by adding 8 expression criteria.
http://www.intelligententerprise.com/000515/webhouse.shtml
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A Definition of Data Warehousing
Michael Reed of TechnologyEvaluation.Com gives a brief overview of the definition of a data warehouse.
http://idm.internet.com/features/datawarehousing.html
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Factless Fact Tables
DBMS Online article by Ralph Kimball discussing two types of useful fact tables that contain no facts at all.
http://www.dbmsmag.com/9609d05.html
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Surrogate Keys
DBMS Online article by Ralph Kimball about keeping control over record identifiers by generating new keys for the data.
http://www.dbmsmag.com/9805d05.html
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Monster Dimensions
DBMS Online article by Ralph Kimball discussing design solutions for handling changes in very large dimensions.
http://www.dbmsmag.com/9605d05.html
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Managing Meta Data Within and Across Warehousing Efforts
Many organizations must manage multiple warehousing initiatives underway simultaneously and these systems will most likely be based on products from multiple data warehousing vendors, in the typical decentralized approach of most corporations.
http://www.tdan.com/i013hy02.htm
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How to do a Warehouse Assessment (And Why)
Arthur Moore and David Wells. The essence of data warehousing assessment is directed at refining the warehousing process and revitalizing the warehousing initiative.
http://www.tdan.com/i013fe03.htm
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Many Alternate Realities
Intelligent Enterprise Magazine article by Ralph Kimball on the data warehouse design challenge of describing the past accurately.
http://www.intelligententerprise.com/000209/webhouse.shtml
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Refreshment Strategies in the Data Warehouse Environment
William Inmon. Once the data warehouse is built, attention shifts from the building of the data warehouse to the day to day operations of making the data warehouse work.
http://www.billinmon.com/library/articles/dwrefres.asp
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