Star Schema The Complete Reference

For technologists looking for a thorough exploration of the traditional data warehouse star schema, nothing compares to this book. Other reviewers are correct that although works by Ralph Kimball are classics in this space, the content that Adamson provides here is presented in much greater detail with a far greater quantity of examples, and written very well. While I found myself referencing "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by the aforementioned author during a recent data warehouse project, because that resource is introductory many practitioners will likely end up referring to the design tips that The Kimball Group website offers as supplementary material on a more frequent basis, and many of these design tips are really only a point in the right direction.So to get to the point, Adamson offers great advice and explicit step-by-step explanations for many star schema topics. The only area that the author does not delve into is material around specific database products, but readers should be able to research this information after following along with the presentation that the author offers with this work. After discussing the fundamentals of analytic databases and dimensional design, data warehouse architectures, and stars and cubes, the author offers detailed presentations on fact tables, dimensions, hierarchies, bridges, snowflakes, and slowly changing dimensions, followed by discussions on performance and additional topics of interest for developers of dimensional models, including an exploration of some common dimensional features that often strain business intelligence tools, techniques to mitigate any shortcomings, and short discussions on process, design, and documentation.One great example of the thoroughness of this book is the presentation that the author offers in Chapter 10 ("Recursive Hierarchies and Bridges"). After discussing types of recursive hierarchies (balanced versus unbalanced and attribute-based versus instance-based), reporting challenges associated with recursive hierarchies, and the process and implications with flattening such hierarchies, Adamson delves into the hierarchy bridge, providing a detailed walkthrough of how to construct it and use it, how to avoid double-counting, how to hide the bridge from novice users, how to resolve the many-to-many relationship, and how to handle Type 2 changes to the hierarchy. The step-by-step explanation of this last item is especially well done, with great diagrams and a detailed discussion of the ripple effect of such changes and why you should not resist the ripple effect, despite the additional data involved. This explanation contrasts markedly with other material on this subject. While a single design tip called "Help for Hierarchies" from The Kimball Group, for example, discusses this subject, it is done so at a very high level.As a data architect working through this book for the first time during a project, most of my time was spent in Part 3 ("Dimensional Design"), which breaks down into Chapter 6 ("More on Dimensional Tables"), Chapter 7 ("Hierarchies and Snowflakes"), Chapter 8 ("More Slow Change Techniques"), Chapter 9 ("Multi-Valued Dimensions and Bridges"), and Chapter 10 ("Recursive Hierarchies and Bridges"), although I did spend significant time with Chapter 4 ("A Fact Table for Each Process"), Chapter 11 ("Transactions, Snapshots, and Accumulating Snapshots"), and Chapter 12 ("Factless Fact Tables"). While I will likely continue to reference a number of other resources in this space, this is the one book currently in the marketplace that has staying power for the long-term. Highly recommended.

The book is broken down into six parts: I. Fundamentals II. Multiple Stars III. Dimension Design IV. Fact Table Design V. Performance VI. Tools and DocumentationThis is a very natural and logical progression through data modeling and ETL implications. You can read the book from beginning to end and/or use it as a reference when faced with a particular challenge. Star Schema covers a wide range of scenarios with examples that can be easily extrapolated to other industries or your particular data.Even being in IT, IT books can be dry. However, Christopher’s writing style is that of a mentor. He walks you through each topic with examples. Often, I came up with a question only to be answered on the next page. This keeps the reader engaged and that makes for a deeper understanding of the material. Not every Customer Dimension or Sales Fact is modeled the same. After you know the concepts and the data, you can produce the best design.From Conformed Dimensions to Recursive Hierarchies and Bridges, you will see your data and your data model in a new light. Every system needs a strong foundation. This book will help you develop a solid dimensional model that will support and grow as your business does.

This book is a must have for anyone involved in dimensional modelling. I've been modelling relational databases for decades so the idea of redundant data was a mind hurdle that I needed to get over. Adamson did a great job of helping me with that by his practical and unbiased explanations of the pros and cons of the dimensional approach. The book is well organized for reading end to end and also provides a great reference while in the development process. I've had my copy for only 2 months and it's well worn by my constant usage. This book has provided exactly what I needed to completely understand the advantages and disadvantages of various approaches to solve real world business problems with the dimensional model. Adamson is obviously very experienced in this technology, is an excellent writer and has a great website for staying current on this subject.

This book really deserves its 5 stars. It is, by far, the best book on data warehousing I have ever read.Not only is the content very precise and comprehensive, but it is also very well written.Data Warehousing concepts are notoriously difficult to explain. That's why so many well-meaning DW books comes short. If you can only read one book on DW design, then make it this one.Contrary to the title, the book covers Snowflake Schema quite adeptly, and the author is careful to list all the pros and cons of going from Star to Snowflake. That leap from star to snowflake should always be taken with considerable thought.The book is light both on data analytics and ETL. This book is almost all about Star and Snowflake schemas.Pros:1)The best book on data warehousing design I have ever read.2)Comprehensive AND in-depth coverage of both Star and Snowflake schemas.3)Very well written.Cons:1)Doesn't cover much outside of data warehousing. It has light coverage of data analytics and ETL.

I have been working designing and developing OLTP databases for 20 years. I am new to Data warehouses and picked up this book based on reviews and I don't have any regrets. I have completed 4 out of 18 chapters ~ 85 pages. I love the way Chris analyses each topic from different angles and explains the pros and cons of each approach. I am fully satisfied with this purchase and would say that this is a great book to clear the concepts of database design for warehouses, which, is very different from OLTP designs.This book does not show how to use a tool. It is purely design concepts. If you are looking for a book that shows how to use a tool, you are looking at the wrong stuff.

This is an excellent excellent book. A real gem that will literally solve almost all your datawarehousing / BI projects biggest problems.Getting the right data model and knowing about different modelling methodologies to reference and quote in meetings is far far more powerful than people realise.

Helped me a lot in college!

A must have

I work in the BI and Analytics area, this is a great overall reference for first timers and experienced professionals

I compared this good to the other star schema books or data warehousing. This is the best of the besteasy to follow along. good diagrams. this is better then the other books the one from the bill inum? is harder toi understand. the person that wrote this book was a student of that guy. this person did a better job to explain + you do not need to cross reference pages as all explanations are given linearly. the other book jumped all over the place and it was harder to follow. I took the Data warehouse workshop at BCIT and loved this book. Its actually worth a read when dealing sql database. People taking a data quality course should also get this book as it teaches you how to organize your data and make it useful for business.