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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

Banking Case Study and Bus Matrix

The bank’s initial goal is to better analyze the bank’s accounts. Business users want the ability to slice and dice individual accounts, as well as the residential household groupings to which they belong. One of the bank’s major objectives is to market more effectively by offering additional products to households that already have one or more accounts with the bank. Figure 10-1 illustrates a portion of a bank’s bus matrix.

image

Figure 10-1: Subset of bus matrix rows for a bank.

After conducting interviews with managers and analysts around the bank, the following set of requirements were developed:

  • Business users want to see five years of historical monthly snapshot data on every account.
  • Every account has a primary balance. The business wants to group different types of accounts in the same analyses and compare primary balances.
  • Every type of account (known as products within the bank) has a set of custom dimension attributes...
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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The Data Warehouse Toolkit
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