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

The previous chapter introduced 34 subsystems that are possible within a comprehensive ETL implementation. In this chapter, we provided detailed practical advice for actually building and deploying the ETL system. Perhaps the most interesting perspective is to separate the initial historical loads from the ongoing incremental loads. These processes are quite different.

In general we recommend using a commercial ETL tool as opposed to maintaining a library of scripts, even though the ETL tools can be expensive and have a significant learning curve. ETL systems, more than any other part of the DW/BI edifice, are legacy systems that need to be maintainable and scalable over long periods of time and over changes of personnel.

We concluded this chapter with some design perspectives for real-time (low latency) delivery of data. Not only are the real-time architectures different from conventional batch processing, but data quality is compromised as the latency is progressively lowered...