Book Image

The Data Warehouse Toolkit - Third Edition

By : Ralph Kimball, Margy Ross
5 (2)
Book Image

The Data Warehouse Toolkit - Third Edition

5 (2)
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
1
Cover
2
Title Page
3
Copyright
4
About the Authors
5
Credits
6
Acknowledgements
29
Index
30
Advertisement
31
End User License Agreement

9
Human Resources Management

This chapter, which focuses on human resources (HR) data, is the last in the series dealing with cross-industry business applications. Similar to the accounting and finance data described in Chapter 7: Accounting, HR information is disseminated broadly throughout the organization. Organizations want to better understand their employees’ demographics, skills, earnings, and performance to maximize their impact. In this chapter we’ll explore several dimensional modeling techniques in the context of HR data.

Chapter 9 discusses the following concepts:

  • Dimension tables to track employee profile changes
  • Periodic headcount snapshots
  • Bus matrix for a snippet of HR-centric processes
  • Pros and cons of packaged DW/BI solutions or data models
  • Recursive employee hierarchies
  • Multivalued skill keyword attributes handled via dimension attributes, outriggers, or bridges
  • Survey questionnaire data
  • Text comments