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Star Schema The Complete Reference
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Star Schema The Complete Reference

Book Details

Format Paperback / Softback
ISBN-10 0071744320
ISBN-13 9780071744324
Publisher McGraw-Hill Education - Europe
Imprint Osborne/McGraw-Hill
Country of Manufacture US
Country of Publication GB
Publication Date Sep 16th, 2010
Print length 510 Pages
Weight 918 grams
Dimensions 23.00 x 18.60 x 2.60 cms
Product Classification: Data warehousing
Ksh 7,000.00
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Filled with expert techniques and best practices, this comprehensive guide helps you unleash the full potential of data warehouses, regardless of architecture, implementation scope, or software tools.

Publisher''s Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.


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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