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

Recursive Employee Hierarchies

A common employee characteristic is the name of the employee’s manager. You could simply embed this attribute along with the other attributes in the employee dimension. But if the business users want more than the manager’s name, more complex structures are necessary.

One approach is to include the manager’s employee key as another foreign key in the fact table, as shown in Figure 9-5. This manager employee key joins to a role-playing employee dimension where every attribute name refers to “manager” to differentiate the manager’s profile from the employee’s. This approach associates the employee and their manager whenever a row is inserted into a fact table. BI analyses can easily filter and group by either employee or manager attributes with virtually identical query performance because both dimensions provide symmetrical access to the fact table. The downside of this approach is these dual foreign keys must...