The Kimball Group Reader
Relentlessly Practical Tools for Data Warehousing and Business Intelligence
By Ralph Kimball, Margy Ross
Publisher: Wiley
Final Release Date: February 2010
Pages: 816

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

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

The Reader begins with a group of articles that established thecore insights and principles of data warehousing. The content thatfollows provides detailed guidance for every step of the datawarehouse lifecycle, with in-depth, practical guidance that you canleverage for your own projects. After covering project planning andbusiness requirements, the authors take a dive into all thingsdimensional. There are more than 100 articles on dimensionalmodeling alone. These articles have been fully revised, updated,and expanded where needed to reflect current best practicesestablished by the Kimball Group.

With incomparable articles providing critical advice forsuccessfully designing, deploying, and maintaining the DW/BIsystem, The Kimball Group Reader covers:

  • Dos and Don'ts for gathering requirements

  • The Kimball enterprise data warehouse architecture andmatrix

  • 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 andragged variable hierarchies

  • Nuances encountered in customer dimensions andinternationalization 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, andpackaged analytics

  • Front-room BI applications and data mining

  • Techniques for assessing a mature DW/BW environment and gettingit back on track

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