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

Summary

In this chapter, we focused primarily on financial data in the general ledger, both in terms of periodic snapshots as well as journal entry transactions. We discussed the handling of common G/L data challenges, including multiple currencies, multiple fiscal years, unbalanced organizational trees, and the urge to create to-date totals.

We used the familiar organization rollup structure to show how to model complex ragged hierarchies of indeterminate depth. We introduced a special bridge table for these hierarchies, and compared this approach to others.

We explored the series of events in a budgeting process chain. We described the use of “net change” granularity in this situation rather than creating snapshots of the budget data totals. We also discussed the concept of consolidated fact tables that combine the results of separate business processes when they are frequently analyzed together.

Finally, we discussed the natural fit of OLAP products for financial analysis...