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The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling by [Kimball, Ralph, Ross, Margy]
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The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling Kindle Edition

4.1 out of 5 stars 15 customer reviews

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Product Description

From the Back Cover

The most authoritative and comprehensive guide to dimensional modeling, from its originators fully updated

Ralph Kimball introduced the industry to the techniques of dimensional modeling in the first edition of The Data Warehouse Toolkit (1996). Since then, dimensional modeling has become the most widely accepted approach for presenting information in data warehouse and business intelligence (DW/BI) systems. The Data Warehouse Toolkit is recognized as the definitive source for dimensional modeling techniques, patterns, and best practices.

This third edition of the classic reference delivers the most comprehensive library of dimensional modeling techniques ever assembled. Fully updated with fresh insights and best practices, this book provides clear guidelines for designing dimensional models and does so in a style that serves the needs of those new to data warehousing as well as experienced professionals.

All the techniques in the book are illustrated with real–world case studies based on the authors′ actual DW/BI design experiences. In addition, the Kimball Group′s "official" list of dimensional modeling techniques is summarized in a single chapter for easy reference, with pointers from each technique to the case studies where the concepts are brought to life.

The third edition of The Data Warehouse Toolkit covers:

  • Practical design techniques both basic and advanced for dimension and fact tables
  • 14 case studies, including retail sales, electronic commerce, customer relationship management, procurement, inventory, order management, accounting, human resources, financial services, healthcare, insurance, education, telecommunications, and transportation
  • Sample data warehouse bus matrices for 12 case studies
  • Dimensional modeling pitfalls and mistakes to avoid
  • Enhanced slowly changing dimension techniques type 0 through 7
  • Bridge tables for ragged variable depth hierarchies and multivalued attributes
  • Best practices for Big Data analytics
  • Guidelines for collaborative, interactive design sessions with business stakeholders
  • An overview of the Kimball DW/BI project lifecycle methodology
  • Comprehensive review of extract, transformation, and load (ETL) systems and design considerations
  • The 34 ETL subsystems and techniques to populate dimension and fact tables

About the Author

RALPH KIMBALL, PhD, has been a leading visionary in the data warehouse and business intelligence industry since 1982. The Data Warehouse Toolkit book series have been bestsellers since 1996.

MARGY ROSS is President of the Kimball Group and the coauthor of five Toolkit books with Ralph Kimball. She has focused exclusively on data warehousing and business intelligence for more than 30 years.


Product details

  • Format: Kindle Edition
  • File Size: 16607 KB
  • Print Length: 601 pages
  • Page Numbers Source ISBN: 1118530802
  • Publisher: Wiley; 3 edition (1 July 2013)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B00DRZX6XS
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Not Enabled
  • Average Customer Review: 4.1 out of 5 stars 15 customer reviews
  • Amazon Bestsellers Rank: #120,819 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Customer Reviews

4.1 out of 5 stars
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Top Customer Reviews

Format: Paperback
Back in the day, this was one of my most-referenced references.

If you work exclusively in relational data warehouses, such as Oracle RDBMS, then it's indispensable. It is still brilliant, and if you want to be a serious BI practitioner, you need to /know/ this text back to front. You need to know it *today*.

But times have moved on. I haven't built a presentation layer for seven years that was based on a /relational/ data warehouse. I still build 'em; it's just that they're only feeders for multidimensional hypercubes.

Back in 2002 I used Analysis Services to build a hypercube with 100 million sales and stock facts for a big retailer. It had a couple of seconds response time. Three years later we were writing sophisticated predictive analytics with multidimensional extensions (MDX).

There's no mention of this in the book. Solid on ETL, great on some industry-standard structures (but see stuff by Len Silverston et al), there's no question any aspiring BI person needs to know everything in here. But it's not enough.

I want to see this book updated to describe how to create a physical non-indexed DW as a feeder for a hypercube. I want to see the power and speed advantages of hypercubes described. I want to hear about the dramatic improvements in the presentation layer possible through the use of MDX. I want to hear about the security and /organisational/ issues involved in allowing reporting developers access to the presentation layer.

In short, as a new edition, this seems to fall a bit short. Still recommended, but . . .
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Format: Paperback
This is a long overdue reincarnation of Kimball's earlier 2nd edition. This edition continues with same format (the reading at places can be boring).

The new additions which are worth mention is that inclusion of chapters where Kimball actually advocated usage of hybrid approach (Inmon & Kimball together) and where he explained end to end project management phases of a large BI/DWH programs.

There were some verbose chapters on ETL technology as well.

There was a chapter on Big Data but it felt like an afterthough only to be mentioned in blurb. The book does not cover how data modelling differs in Big Data world. Technically it does cover, but not with examples as main part of book was written for RDBMS world.

May be that will happen in 4th edition of the book!
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Format: Kindle Edition
This book can take you from having no idea about how to implement a data warehouse to having a complete data model implemented that will support your business users needs.

The book includes some introductory details about the planning and management of your data warehouse/business intelligence project and also about the ETL process to populate your model - but you will need to read other books to complete your knowledge on those subjects.
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Format: Kindle Edition Verified Purchase
This was recommended to me as a must read and the de facto bible for data warehousing projects. Maybe I expected to much after the enthusiastic recommendation but I found the book an absolute bore with very little useful information. There is little depth to actual concrete process, technical designs or even guidance with too many references to their other books or website. Quite frankly, you could probably summarise the key points on 2 to 3 pages but the author manages to string it out to a whopoping 600. Very disappointed.
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By DBA on 26 Jun. 2016
Format: Paperback Verified Purchase
Excellent reference book, useful examples and guidance,
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Format: Paperback Verified Purchase
Excellent for getting a firm grasp on Kimball methodologies however it can be quite hard to keep your attention with it long winded explanations
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Format: Kindle Edition Verified Purchase
The go to book for datawarehousing.. Reads very well and each section has a bunch of relevant examples... Can't go wrong purchasing this...
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Format: Paperback
i think is well explained, easy to understand, but i haven't finished yet
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