The Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence

Overview

A collection of the most authoritative, detailed, and practical guidelines for data warehousing and business intelligence

Over the past 15 years, Ralph Kimball and his unparalleled team of colleagues have written articles covering more than 250 topics that have come to define the field of data warehousing (DW). The Kimball Group Reader presents the best of these articles, fully updated to reflect their current thinking and practices. Covering the complete lifecycle—including project planning, requirements gathering, dimensional modeling, ETL, and business intelligence (BI) and analytics—the authors provide detailed, technical guidance that expands beyond the Toolkit essentials to provide fresh insights and best practices.

The Reader begins with a group of articles that established the core insights and principles of data warehousing. The content that follows provides detailed guidance for every step of the data warehouse lifecycle, with in-depth, practical guidance that you can leverage for your own projects. After covering project planning and business requirements, the authors take a dive into all things dimensional. There are more than 100 articles on dimensional modeling alone. These articles have been fully revised, updated, and expanded where needed to reflect current best practices established by the Kimball Group.

With incomparable articles providing critical advice for successfully designing, deploying, and maintaining the DW/BI system, The Kimball Group Reader covers:

• Dos and Don'ts for gathering requirements
• The Kimball enterprise data warehouse architecture and matrix
• Dimensional modeling tasks and responsibilities
• Fact table and dimension table core concepts
• Data stewardship for conforming dimensions
• Granularity and three fundamental types of fact tables
• Snowflakes and outriggers
• Bridges for handling multi-valued dimension attributes and ragged variable hierarchies
• Nuances encountered in customer dimensions and internationalization issues
• Slowly changing dimensions and hybrid variations
• Subsystems to extract, transform, and load (ETL) data
• Pros and cons of using a commercial ETL tool
• Server-oriented architecture, master data management, and packaged analytics
• Front-room BI applications and data mining
• Techniques for assessing a mature DW/BW environment and getting it back on track

Read More