This revised and updated edition of the bestseller provides a complete library of dimensional modeling techniques, the most comprehensive collection ever written.
The most authoritative and comprehensive guide to dimensional modeling, from its originators-fully updated
Ralph Kimball introduced the industry to the techniques of dimensional modeling in the first edition of The Data Warehouse Toolkit (1996). Since then, dimensional modeling has become the most widely accepted approach for presenting information in data warehouse and business intelligence (DW/BI) systems. The Data Warehouse Toolkit is recognized as the definitive source for dimensional modeling techniques, patterns, and best practices.
This third edition of the classic reference delivers the most comprehensive library of dimensional modeling techniques ever assembled. Fully updated with fresh insights and best practices, this book provides clear guidelines for designing dimensional models-and does so in a style that serves the needs of those new to data warehousing as well as experienced professionals.
All the techniques in the book are illustrated with real-world case studies based on the authors' actual DW/BI design experiences. In addition, the Kimball Group's "official" list of dimensional modeling techniques is summarized in a single chapter for easy reference, with pointers from each technique to the case studies where the concepts are brought to life.
The third edition of The Data Warehouse Toolkit covers:
- Practical design techniques-both basic and advanced-for dimension and fact tables
- 14 case studies, including retail sales, electronic commerce, customer relationship management, procurement, inventory, order management, accounting, human resources, financial services, healthcare, insurance, education, telecommunications, and transportation
- Sample data warehouse bus matrices for 12 case studies
- Dimensional modeling pitfalls and mistakes to avoid
- Enhanced slowly changing dimension techniques type 0 through 7
- Bridge tables for ragged variable depth hierarchies and multivalued attributes
- Best practices for Big Data analytics
- Guidelines for collaborative, interactive design sessions with business stakeholders
- An overview of the Kimball DW/BI project lifecycle methodology
- Comprehensive review of extract, transformation, and load (ETL) systems and design considerations
- The 34 ETL subsystems and techniques to populate dimension and fact tables
