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Compare Book Prices and get the Cheapest UK Price for 'The Data Warehouse Toolkit: The Complete Guide to Dimensional Modelling' by Ralph Kimball. |
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Description | The latest edition of the single most authoritative guide on dimensional modeling for data warehousing! Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: * Retail sales and e-commerce * Inventory management * Procurement * Order management * Customer relationship management (CRM) * Human resources management * Accounting * Financial services * Telecommunications and utilities * Education * Transportation * Health care and insurance 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. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts. This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books: The Data Warehouse Toolkit, 2nd Edition (9780471200246) The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775) The Data Warehouse ETL Toolkit (9780764567575) | Release Date | 2002-04-26 | Author | Ralph Kimball Margy Ross | Format | Dimensions 18.9x24.0x2.5 cm 472 pages book | Publisher | Wiley | Subject(s) | Computers / Data Science / Data Warehousing Computers / Information Technology |
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Last Updated 25/11/2024 at 04:00. |
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