Book Image

The Data Warehouse Toolkit - Third Edition

By : Ralph Kimball, Margy Ross
5 (1)
Book Image

The Data Warehouse Toolkit - Third Edition

5 (1)
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
Title Page
About the Authors
End User License Agreement

Special Purpose Schemas

The following design patterns are needed for specific use cases.

Supertype and Subtype Schemas for Heterogeneous Products

Financial services and other businesses frequently offer a wide variety of products in disparate lines of business. For example, a retail bank may offer dozens of types of accounts ranging from checking accounts to mortgages to business loans, but all are examples of an account. Attempts to build a single, consolidated fact table with the union of all possible facts, linked to dimension tables with all possible attributes of these divergent products, will fail because there can be hundreds of incompatible facts and attributes. The solution is to build a single supertype fact table that has the intersection of the facts from all the account types (along with a supertype dimension table containing the common attributes), and then systematically build separate fact tables (and associated dimension tables) for each of the subtypes. Supertype and...