Mastering Data Warehouse Design
Relational and Dimensional Techniques
By Claudia Imhoff, Nicholas Galemmo, Jonathan G. Geiger
Publisher: Wiley
Final Release Date: August 2003
Pages: 456

At last, a balanced approach to data warehousing that leverages thetechniques pioneered by Ralph Kimball and Bill Inmon

Since its groundbreaking inception, the approach tounderstanding data warehousing has been split into two mindsets:Ralph Kimball, who pioneered the use of dimensional modelingtechniques for building the data warehouse, and Bill Inmon, whointroduced the Corporate Information Factory and leads those whobelieve in using relational modeling techniques for the datawarehouse. Mastering Data Warehouse Design successfully mergesInmon’s data ware- house design philosophies withKimball’s data mart design philosophies to provide you with acompelling and complete overview of exactly what is involved indesigning and building a sustainable and extensible datawarehouse.

Most data warehouse managers, designers, and developers arefamiliar with the open letter written by Ralph Kimball in 2001 tothe data warehouse community in which he challenged those in theInmon camp to answer some tough questions about the effectivenessof the relational approach. Cowritten by one of the best-knownexperts of the Inmon approach, Claudia Imhoff, this team of authorsaddresses head-on the challenging questions raised by Kimball inhis letter and offers a how-to guide on the appropriate use of bothrelational and dimensional modeling in a comprehensive businessintelligence environment. In addition, you’ll learn theauthors’ take on issues such as:

  • Which approach has been found most successful in data warehouseenvironments at companies spanning virtually all major industrialsectors
  • The pros and cons of relational vs. dimensional modelingtechniques so developers can decide on the best approach for theirprojects
  • Why the architecture should include a data warehouse built onrelational data modeling concepts
  • The construction and utilization of keys, the historical natureof the data warehouse, hierarchies, and transactional data
  • Technical issues needed to ensure that the data warehousedesign meets appropriate performance expectations
  • Relational modeling techniques for ensuring optimum datawarehouse performance and handling changes to data over time
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