The Data Warehouse Toolkit, 3rd Edition
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Ralph Kimball and Margy Ross co-authored The Data Warehouse Toolkit, Third Edition (Wiley, 2013). This definitive guide provides a complete collection of dimensional modeling techniques, beginning with fundamental concepts and gradually progressing through increasingly complex real-world case studies.

The book significantly enhances and expands upon the concepts and examples presented in the earlier editions of The Data Warehouse Toolkit.

  • “Official” glossary of more than 80 Kimball dimensional modeling techniques
  • Expanded coverage of advanced dimensional modeling patterns for more complex real-world scenarios, including bridge tables for ragged variable depth hierarchies and multivalued attributes
  • Sample data warehouse bus matrices for 12 case studies
  • Enhanced slowly changing dimension techniques type 0 through 7
  • Recommended best practices for big data analytics
  • Guidance regarding collaborative, interactive dimensional modeling design sessions with business stakeholders
  • Updated overview of the Kimball DW/BI project lifecycle methodology
  • Comprehensive review of extract, transformation, and load (ETL) systems and design considerations, including 34 subsystems and techniques to populate dimensional models

Tools and Utilities

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Chapter 3

Sample date dimension spreadsheet

DownloadSample date dimension spreadsheet

Correction to Figure 3-13: The first heading in the lower report shown in Figure 3-13 should read “Calendar Week Ending Date,” just like the top report in that figure.

Correction to text at top of page 100 under Dimension Table Surrogate Keys heading: It has 32 bits and therefore can handle approximately 4 billion unsigned positive values (232) or 4 billion total positive and negative values (-231 to 231-1).

Chapter 4

Correction to text beneath Figure 4-3: The only fully additive metric in the figure is Quantity Sold. The Quantity on Hand and inventory valuation metrics are semi-additive as they can’t be simply summed over time periods; you would want to divide the sum by the number of daily observations to arrive at an average inventory balance or valuation.

Chapter 10

Correction to Figure 10-4: The Customer Key in the far right table of Figure 10-4 should be designated as a primary key (PK), not a foreign key (FK).