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The Data Warehouse Toolkit

The Data Warehouse Toolkit - Third Edition

By : Ralph Kimball, Margy Ross
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The Data Warehouse Toolkit

The Data Warehouse Toolkit

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)
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1
Cover
2
Title Page
3
Copyright
4
About the Authors
5
Credits
6
Acknowledgements
29
Index
30
Advertisement
31
End User License Agreement

ETL Process Overview

This chapter follows the flow of planning and implementing the ETL system. We implicitly discuss the 34 ETL subsystems presented in Chapter 19: ETL Subsystems and Techniques, broadly categorized as extracting data, cleaning and conforming, delivering for presentation, and managing the ETL environment.

Before beginning the ETL system design for a dimensional model, you should have completed the logical design, drafted your high-level architecture plan, and drafted the source-to-target mapping for all data elements.

The ETL system design process is critical. Gather all the relevant information, including the processing burden the extracts will be allowed to place on the operational source systems, and test some key alternatives. Does it make sense to host the transformation process on the source system, target system, or its own platform? What tools are available on each, and how effective are they?

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