The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
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. Get and download textbook The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling for free
Cowritten by Ralph Kimball, the world's leading data warehousing authority Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality 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)
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 The Data Warehouse Toolkit new edition
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The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling: Margy Ross, Ralph Kimball
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The Data Warehouse Toolkit Textbook
Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from