Mastering Data Warehouse Design: Relational and Dimensional Techniques by Claudia Imhoff, Jonathan G. Geiger, Nicholas Galemmo

Mastering Data Warehouse Design: Relational and Dimensional Techniques



Download Mastering Data Warehouse Design: Relational and Dimensional Techniques

Mastering Data Warehouse Design: Relational and Dimensional Techniques Claudia Imhoff, Jonathan G. Geiger, Nicholas Galemmo ebook
Publisher: Wiley
Format: pdf
Page: 456
ISBN: 9780471324218


Aug 27, 2010 - Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems * Weighs the pros and cons of relational vs. Jul 27, 2010 - Mastering Data Warehouse Design : Relational and Dimensional Claudia Imhoff | 2008 | 456 pages | PDF | 37.7.5 MB A cutting-edge response to Ralph Kimball's challenge to the data warehouse. Oct 15, 2002 - By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. Dec 18, 2006 - Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems * Weighs the pros and cons of relational vs. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management By Gordon S. Geiger This book provides a thorough grounding in Data Warehouse design. Mastering Data Warehouse Design: Relational and Dimensional Techniques. Mastering Data Warehouse Design: Relational and Dimensional Techniques book download. Dec 11, 2013 - Mastering Data Warehouse Design: Relational and Dimensional Techniques Free eBook Download. Feb 2, 2009 - Mastering Data Warehouse Design: Relational and Dimensional Techniques by Claudia Imhoff, Nicholas Galemmo, and Jonathan G. Apr 17, 2013 - Tuesday, 16 April 2013 at 15:19. Jul 22, 2013 - Fully updated with fresh insights and best practices, this book provides clear guidelines for designing dimensional models—and does so in a style that serves the needs of those new to data warehousing as well as experienced professionals.

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