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Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing: Delivering the Promise of Business Intelligence (Agile Software Development) Paperback – 27 Jul 2011

2.5 out of 5 stars 2 customer reviews

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“This book does a great job of explaining why and how you would implement Agile Analytics in the real world. Ken has many lessons learned from actually implementing and refining this approach. Business Intelligence is definitely an area that can benefit from this type of discipline.”

―Dale Zinkgraf, Sr. Business Intelligence Architect


“One remarkable aspect of Agile Analytics is the breadth of coverage―from product and backlog management to Agile project management techniques, from self-organizing teams to evolutionary design practices, from automated testing to build management and continuous integration. Even if you are not on an analytics project, Ken’s treatment of this broad range of topics related to products with a substantial data-oriented flavor will be useful for and beyond the analytics community.”

―Jim Highsmith, Executive Consultant, ThoughtWorks, Inc., and author of Agile Project Management


“Agile methods have transformed software development, and now it’s time to transform the analytics space. Agile Analytics provides the knowledge needed to make the transformation to Agile methods in delivering your next analytics projects.”

―Pramod Sadalage, coauthor of Refactoring Databases: Evolutionary Database Design


“This book captures the fundamental strategies for successful business intelligence/analytics projects for the coming decade. Ken Collier has raised the bar for analytics practitioners―are you up to the challenge?”

―Scott Ambler, Chief Methodologist for Agile and Lean, IBM Rational Founder, Agile Data Method


“A sweeping presentation of the fundamentals that will empower teams to deliver high-quality, high-value, working business intelligence systems far more quickly and cost effectively than traditional software development methods.”

―Ralph Hughes, author of Agile Data Warehousing

About the Author

Ken Collier has worked with Agile methods since 2003, and pioneered the integration of Agile methods with data warehousing, business intelligence, and analytics to create the Agile Analytics style. He continues to refine these ideas as technical lead and project manager on several Agile DW/BI project teams. Collier frequently trains DW/BI teams in Agile Analytics, and has been a keynote speaker on the subject at HEDW (Higher Education Data Warehouse) 2011 and multiple TDWI (The Data Warehousing Institute) World Conferences. He is founder and president of KWC Technologies, Inc., and a senior consultant in the Cutter Consortium’s Agile Development and Business Intelligence practice areas.

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Format: Paperback
As with most data professionals I wrestle with how to apply agile principles and practises on large datasets on an ongoing basis. As data warehousing and business intelligence are my particular focus I was drawn to this book. but sadly I cannot recommend it.
* It has nothing to do with analytics
* The majority of it is vanilla agile practises and nothing to do with BI/Data warehousing
* It fails to mention what must surely be the prime concern of any BI system, DATA QUALITY
* It completely misses any data profiling activity or data exploration activity
* Where BI is mentioned it is given a very shallow treatment.
* It scatters references to Inmon and Kimball but fails to weave their work into the books theme or deal with conflicts between the agile method proposed and the methods by the fathers of data warehousing/dimensional modelling.

For example, Kimball warns against building a system to produce a particular report as this produces a stovepipe solution. Model the business process correctly and this will provide the solid foundation on which the report (and reports yet to be conceived) will be built. You don't have to model the foundation for the entire house but you do have to build the foundations in a way that is robust enough and extensible enough to prevent stovepiping. The book does not address or discuss the apparent conflict between its message and Kimball's approach.

There is one useful idea in it and that is using a message based architecture for populating the data warehouse. However it then explicitly describes the use of an entity-attribute-value database to provide an agile method of building a long term system of record.
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Format: Paperback
If your business intelligence team has discussed "going agile", this book can give you practical information to help you get there. It's refreshing to see that business intelligence and analytics professionals can adopt practices typically associated with Java, Ruby, and Objective-C developers.

The book is organized into two sections, management methods and technical methods. Most of the technical methods focus on data modeling and data integration (often referred to as Extract, Transform, and Load, or ETL). While these areas are critical to a successful business intelligence system, my role is most often focused on the presentation layer or BI toolset (such as SAP BusinessObjects). So I personally gravitated toward the first half of the book, management methods.

Ken says more than once that the whole point of agile is to "be agile", not just to "do agile". Unfortunately, "agile" can be overused as the latest management buzzword to dress up "hacking" or "unrealistic deadlines". I was actually surprised to read that agile may not improve delivery times. In the short term, delivery times may increase. But the payoff for agility is projects that more quickly respond to changing requirements and users that receive smaller functional deliveries instead of the "big bang" of the waterfall project death march.

While the book is a well-written and easy to read, I found it necessary to read slowly, chapter by chapter, and reflect on what I had read. The book would easily lend itself to a weekly BI book club, where technicians, users, and management meet weekly to discuss the book one chapter at a time. Recommended reading.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 4.1 out of 5 stars 15 reviews
4.0 out of 5 stars A very nice approach of the real world of analytics 14 Oct. 2016
By Reinaldo Maciel - Published on Amazon.com
Format: Paperback Verified Purchase
A very nice approach of the real world of analytics. Mr. Collier is very didatic with his examples and with the do's and don't do.
5.0 out of 5 stars Useful Concepts 26 Dec. 2014
By JB - Published on Amazon.com
Format: Kindle Edition Verified Purchase
Smart framing of analytics in terms of agile methods. A number of useful concepts that I'll incorporate into my everyday work.
2 of 3 people found the following review helpful
4.0 out of 5 stars Good Agile book 16 Mar. 2013
By Paul Kosinski - Published on Amazon.com
Format: Paperback Verified Purchase
My manager read this book and recommended it to our data engineering team as a reference before we started using Agile for an Analytics project. I haven't completed the book but appreciate how the author discusses the challenges of software development then compares and contrasts that with database projects which have tended to be late adopters of Agile.
2 of 4 people found the following review helpful
4.0 out of 5 stars Finally practical advice on how to be agile in BI/DWH projects 2 Jun. 2012
By Daniel Galassi - Published on Amazon.com
Format: Paperback Verified Purchase
Good coverage of agile topics and practices including user stories, team work, project automation and how to introduce agile aspects to BI projects.
There are some practical pieces of advice to improve the way agile software configuration management and agile release management work.
No consulting clutter, no obscure concepts. I clearly identified some of the scenarios and improvement opportunities mentioned in this book from my experience in business intelligence projects.
Some of the practices may be difficult to implement if you are using COTS or off the shelf BI tools, or at least it won't be as easy as described by the author. Case in point: version control and continuous delivery, given the nature of the BI "code".

Overall great description of agile projects. A bit detached from corporate environments in terms of sandpit environments and CD practices in the BI world though, which is understandable.
1 of 2 people found the following review helpful
4.0 out of 5 stars Good introduction and detail on agile analytics 11 Oct. 2012
By Samuel Denson - Published on Amazon.com
Format: Kindle Edition Verified Purchase
Agile Analytics is a good book, especially for someone new to agile BI development. I recommend this book to anyone looking for ways to bridge the gap between agile development and project management for applications and BI.
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