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Star Schema The Complete Reference

Star Schema The Complete Reference

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Author: Christopher Adamson
Publisher: McGraw-Hill Osborne Media
Category: Book

List Price: $59.99
Buy New: $31.68
as of 5/25/2012 17:16 EDT details
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New (23) Used (17) from $29.57

Seller: SuperBookDeals-
Sales Rank: 31,833

Languages: English (Unknown), English (Original Language), English (Published)
Media: Paperback
Edition: 1
Pages: 510
Number Of Items: 1
Shipping Weight (lbs): 1.9
Dimensions (in): 9 x 7.4 x 1

ISBN: 0071744320
EAN: 9780071744324
ASIN: 0071744320

Publication Date: July 7, 2010
Availability: Usually ships in 1-2 business days



Also Available In:

  • Paperback - Star Schema The Complete Reference 1st (first) edition
  • Unknown Binding - Star Schema The Complete Reference [Paperback]
  • Kindle Edition - Star Schema The Complete Reference

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Product Description

The definitive guide to dimensional design for your data warehouse

Learn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts.

This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book progresses through a series of advanced techniques that help you address real-world complexity, maximize performance, and adapt to the requirements of BI and ETL software products. You are furnished with design tasks and deliverables that can be incorporated into any project, regardless of architecture or methodology.

  • Master the fundamentals of star schema design and slow change processing
  • Identify situations that call for multiple stars or cubes
  • Ensure compatibility across subject areas as your data warehouse grows
  • Accommodate repeating attributes, recursive hierarchies, and poor data quality
  • Support conflicting requirements for historic data
  • Handle variation within a business process and correlation of disparate activities
  • Boost performance using derived schemas and aggregates
  • Learn when it's appropriate to adjust designs for BI and ETL tools



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