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Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema, by Lawrence Corr Jim Stagnitto
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Product details
Paperback: 328 pages
Publisher: DecisionOne Press; 42745th edition (November 24, 2011)
Language: English
ISBN-10: 0956817203
ISBN-13: 978-0956817204
Product Dimensions:
8 x 0.7 x 10 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
35 customer reviews
Amazon Best Sellers Rank:
#92,812 in Books (See Top 100 in Books)
I was a Ralph Kimball fan since the late 1990s. In 2012 I came across Lawrence's book. It clarified the process and dimensional design patterns very clearly. In addition, Lawrence was generous about sharing his materials and templates and providing ideas when I contacted him. If you are a BI professional who works directly with business stakeholders and who wants to collaborate effectively, this is the book for you. If you are a dimensional database modeler who wants to know more about dimensional design patterns and when to use them to provide the best product for your users, read this book. If you are a BI professional who simply wants to know what is possible in terms of a flexible, efficient and extensible design, read this book.
Good step-by-step guide for capturing data warehousing requirements and building dimensional models from these requirements through modelstorming (data modeling plus brainstorming) with business intelligence stakeholders. After explaining the difference between online transaction processing and data warehousing, and explaining high-level aspects of the 7Ws framework and the BEAM agile dimensional modeling method in the introductory chapter, the authors discuss modeling business events, business dimensions (the second longest chapter containing about 12% of the text), business processes, and star schemas, followed by design patterns for "who" and "what" (the longest chapter containing about 13% of the text), "when and where", "how many", and "why" and "how", corresponding to the 7Ws.Unlike some other technical texts, the authors really do walk the reader through the material one step at a time, with no skipping around between topics that many readers complain about elsewhere. Other than the step-by-step aspect of this book, another reason I found this book so well put together are the abundant, well-placed diagrams throughout that greatly add to the material. Although what initially got me interested in this text is the agile process surrounding data warehousing, the chapters on dimensional design patterns for performance, flexibility, and usability compliment well the book that I currently consider the best on the traditional data warehouse star schema, "Star Schema: The Complete Reference" by Christopher Adamson (see my review).In the chapter covering "who" and "what" design patterns, for example, the authors cover customer dimensions (particularly challenging because of their typical depth, width, and volatility) alongside the mini-dimension pattern, the sensible snowflaking pattern, swappable dimension patterns, customer relationships, and hierarchy maps, as well as employee dimensions alongside the hybrid slowly changing dimension (SCD) view pattern, the previous value attribute pattern, and the multi-valued hierarchy map pattern, followed by product and service dimensions alongside the multi-level dimension pattern and the parts explosion hierarchy map pattern. And the chapter covering "how" design patterns provides one of the best concise explanations of fact table types and fact types.The one potential issue with this book is that although its goal is agile data warehouse design, getting familiar with the BEAM (business event analysis and modeling) notation used throughout the author discussions might be a bit time prohibitive for teams comprised of more than a few individuals to become accustomed when using for the first time. While the second appendix at the back of the book provides effective short codes for event story and fact table types, dimension table types, general column codes, data types, key types, dimensional attribute types, and event detail and fact column types, some upfront initial team investment will almost certainly be involved for which an agile spike will be needed, and close attention to workability with stakeholders should be assessed. Well recommended overall.
Far and away the most comprehensive, pragmatic, and insightful book on warehouse design I've ever come across. In a dense but approachable (and beautifully written) 300 pages, this book recapitulates and re-examines the accepted canon of work in this space (Kimball, et al), reinvigorating the well-worn fundamentals of data warehouse model design; it's a primer and an expert-level guide in one. Ideas and techniques that have only previously been described in long-winded and subjective prose, are re-examined and made precise and applicable. Applying the core notions from Scott Ambler's Agile Modeling, Gojko Adzic's Specification By Example, and Mike Cohn's User Stories Applied, along with the best of everything Kimball, et al, have ever had to say, the BEAM methodology guides and organizes the practitioner's thinking, providing the recipes and patterns necessary to consistently deliver quality models.
An amazing read. If Kimball's books answer the question "what" you are going to build, Lawrence's BEAM book covers the "how" far in depth and from a far more practical perspective. This is a bible on how to skillfully engage the business stakeholders in the arduous process of understanding their DW/BI expectations.Don't forget to also register at the author's website for very useful tools and templates.
First industry specific book that I felt was not a forced read for me. I've read large parts of the Kimball Desk Reference set :) and various others on the subject of modeling and managing projects of the BI/DW focus, but each felt like a text book compared to how well this has been written and distilled.I've had success in the past with a mentor that has insisted using spreadsheets to tease out data models for OLTP systems, and have found greater success in communicating and capturing designs with less technical audiences. Congratulations on formalizing that approach when Modeling Business Events! I immediately see how this will benefit the entire life-cycle.
I admit that I was a bit jaded about the true effectiveness of Agile and EDW (after all everyone seems to be jumping on the Agile bandwagon and using it as a buzzword). However, after reading this book, I now do see how Agile and EDW could work. It is not a silver bullet for eliminating re-coding or designing a data warehouse that will cover all future reporting needs but it should help in developing a robust, proactive design that anticipates future demand and designs for it.The BEAM* methodology alone was worth the "price of admission". It provides a manner to solicit and capture requirements (using Agile approaches of course) that makes is easier for stakeholders (people who will run and request reports) to articulate requirements. And then, a manner to translate them into Dimensional Models.
This book is not only good, but practical as well. It gives lots of good examples and the author is very willing to send you templates to help get you started. I held an introductory session with my data warehousing team and everyone is eager to give it a go. I tried a quick sample exercise and the team all got involved and started yelling out details for the 7 W's.
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