Book Image

The Data Warehouse Toolkit - Third Edition

By : Ralph Kimball, Margy Ross
Book Image

The Data Warehouse Toolkit - Third Edition

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

Healthcare provides a wealth of dimensional design examples. In this chapter, the enterprise data warehouse bus matrix illustrated the critical linkages between a healthcare organization’s administrative and clinical data. We used an accumulating snapshot grain fact table with role-playing date dimensions for the healthcare claim billing and payment pipeline. We also saw role playing used for the physician and payer dimensions in other fact tables of this chapter.

Healthcare schemas are littered with multivalued dimensions, especially the diagnosis dimension. Complex surgical events might also use multivalued bridge tables to represent the teams of involved physicians and other staff members. The bridge tables used with healthcare data seldom contain weighting factors, as discussed in earlier chapters, because it is extremely difficult to establish weighting business rules, beyond the designation of a “primary” relationship.

We discussed medical records and...