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

Factless Accident Events

We earlier described factless fact tables as the collision of keys at a point in space and time. In the case of an automobile insurer, you can record literal collisions using a factless fact table. In this situation, the fact table registers the many-to-many correlations between the loss parties and loss items, or put in laymen’s terms, all the correlations between the people and vehicles involved in an accident.

Two new dimensions appear in the factless fact table shown in Figure 16-11. The loss party captures the individuals involved in the accident, whereas the loss party role identifies them as passengers, witnesses, legal representation, or some other capacity. As we did in Chapter 3: Retail Sales, we include a fact that is always valued at 1 to facilitate counting and aggregation. This factless fact table can represent complex accidents involving many individuals and vehicles because the number of involved parties with various roles is open-ended...