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

Accumulating Snapshot for Order Fulfillment Pipeline

The order management process can be thought of as a pipeline, especially in a build-to-order manufacturing business, as illustrated in Figure 6-18. Customers place an order that goes into the backlog until it is released to manufacturing to be built. The manufactured products are placed in finished goods inventory and then shipped to the customers and invoiced. Unique transactions are generated at each spigot of the pipeline. Thus far we’ve considered each of these pipeline activities as a separate transaction fact table. Doing so allows you to decorate the detailed facts generated by each process with the greatest number of detailed dimensions. It also allows you to isolate analysis to the performance of a single business process, which is often precisely what the business users want.

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Figure 6-18: Order fulfillment pipeline diagram.

However, there are times when business users want to analyze the entire order fulfillment...