Mastering Data Warehouse Aggregates: Maximizing Star Schema Performance

Overview

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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