Mastering Data Warehouse Aggregates: Solutions for Star Schema...

Features

• Cover Type: Paperback with 384 pages
• Published by: Wiley July 19, 2006
• Written in: English
• ISBN 10 Number: 0471777099
• ISBN 13 Number: 978-0471777090
• Book Dimensions: 9.2 x 7.2 x 0.9 inches
• Weighs: 1.2 pounds

Book Description

• This is the first book to provide in-depth coverage of star schema aggregates used in dimensional modeling-from selection and design, to loading and usage, to specific tasks and deliverables for implementation projects
• Covers the principles of aggregate schema design and the pros and cons of various types of commercial solutions for navigating and building aggregates
• Discusses how to include aggregates in data warehouse development projects that focus on incremental development, iterative builds, and early data loads

Back Cover Copy
The first book to offer in-depth coverage of star schema aggregate tables

Dubbed by Ralph Kimball as the most effective technique for maximizing star schema performance, dimensional aggregates are a powerful and efficient tool that can accelerate data warehouse queries more dramatically than any other technology. After you ensure that a database is properly designed, configured, and tuned, any measures you take to address data warehouse performance should begin with aggregates.

Yet, many businesses ignore aggregates, instead turning to specialized, proprietary hardware and software products to solve performance problems. This book fills the knowledge gap that has led businesses on this expensive and risky path.

Data warehouse expert Chris Adamson shows how a well-planned set of aggregates can have an extraordinary effect on the overall throughput of your data warehouse. Regardless of your role or current level of star schema expertise, the best practices in this book will help you achieve astounding performance increases, while avoiding common pitfalls.

From star schema basics through advanced aggregation techniques, this book covers the impact of aggregate tables on the entire data warehouse lifecycle. After establishing a few fundamentals, including the star schema approach to data warehouse design, chapters are dedicated to major phases of the data warehouse lifecycle. Topics include:

• Fundamental principles of aggregate schema design
• How to use aggregates in a production environment, with or without an aggregate navigator
• Integration of aggregate processing into the ETL process
• Standard tasks and deliverables for incorporating aggregates into data warehouse development projects
• How to organize and execute a project that adds aggregate capability to an existing star schema
• The impact of advanced schema design techniques such as bridge tables, heterogeneous stars, or snapshot models on aggregation
• Special considerations when implementing dimensional aggregates using Oracle's materialized views or IBM's materialized query tables
• How aggregates can add value in other areas, including database security and the archive strategy

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Reader Reviews
Chris does a great job of laying out both the good and bad associated with using aggregates as a means to support Business Intelligence and Hierarchical-type queries within a Data Warehouse environment. As a disciple of Ralph Kimball's Chris kept true to the doctrine and helped the reader understand why he recommended the tacts he did throughout the manuscript. The material was easy to follow and his illustrations were clear representations of the material being presented. I especially liked that he added platform-specific hints and scenarios to tailor the material to the reader's environment. While I do not necessarily agree that building aggregate tables are the solution to many of the challenges in a Business Intelligence use of Data from a Data Warehouse, I do feel that Chris' book is a great place to start to learn the challenges and start down the path of solution to the problem. Add on material might include mention of other solutions that are not manual that also address the same challenge - such as the software package from HyperRoll. Comment | | (Report this)