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

Dealing with Dimension Hierarchies

Dimensional hierarchies are commonplace. This section describes approaches for dealing with hierarchies, starting with the most basic.

Fixed Depth Positional Hierarchies

A fixed depth hierarchy is a series of many-to-one relationships, such as product to brand to category to department. When a fixed depth hierarchy is defined and the hierarchy levels have agreed upon names, the hierarchy levels should appear as separate positional attributes in a dimension table. A fixed depth hierarchy is by far the easiest to understand and navigate as long as the above criteria are met. It also delivers predictable and fast query performance. When the hierarchy is not a series of many-to-one relationships or the number of levels varies such that the levels do not have agreed upon names, a ragged hierarchy technique, described below, must be used.