Book Image

The Data Warehouse Toolkit - Third Edition

By : Ralph Kimball, Margy Ross
5 (1)
Book Image

The Data Warehouse Toolkit - Third Edition

5 (1)
By: Ralph Kimball, Margy Ross

Overview of this book

The volume of data continues to grow as warehouses are populated with increasingly atomic data and updated with greater frequency. Dimensional modeling has become the most widely accepted approach for presenting information in data warehouse and business intelligence (DW/BI) systems. The goal of this book is to provide a one-stop shop for dimensional modeling techniques. The book is authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligence. The book begins with a primer on data warehousing, business intelligence, and dimensional modeling, and you’ll explore more than 75-dimensional modeling techniques and patterns. Then you’ll understand dimension tables in-depth to get a good grip on retailing and moved towards the topics of inventory. Moving ahead, you’ll learn how to use this book for procurement, order management, accounting, customer relationship management, and many more business sectors. By the end of this book, you’ll be able to gather all the essential knowledge, practices, and patterns for designing dimensional models.
Table of Contents (31 chapters)
Free Chapter
Title Page
About the Authors
End User License Agreement


In this chapter, we discussed several concepts in the context of HR data. First, we further elaborated on the advantages of embellishing an employee dimension table. In the world of HR, this single table is used to address a number of questions regarding the status and profile of the employee base at any point in time. We drafted a bus matrix representing multiple processes within the HR arena and highlighted a core headcount snapshot fact table, along with the potential advantages and disadvantages of vendor-designed solutions and data models. The handling of managerial rollups and multivalued dimension attributes was discussed. Finally, we provided a brief overview regarding the handling of survey or questionnaire data, along with text comments.