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Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile Software Development Series) 1st Edition

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ISBN-13: 978-0321504814
ISBN-10: 032150481X
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Editorial Reviews

Review

“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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Product Details

  • Series: Agile Software Development Series
  • Paperback: 368 pages
  • Publisher: Addison-Wesley Professional; 1 edition (August 6, 2011)
  • Language: English
  • ISBN-10: 032150481X
  • ISBN-13: 978-0321504814
  • Product Dimensions: 6.9 x 0.7 x 9.1 inches
  • Shipping Weight: 1.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (13 customer reviews)
  • Amazon Best Sellers Rank: #687,359 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

8 of 10 people found the following review helpful By Shane Willerton on November 11, 2011
Format: Paperback
The Data Warehousing development arena lags behind the application development area as far as adopting project management and development techniques. Some of the common excuses to not even look at Agile adoption include: Data Warehousing is fundamentally different than application development; The first thing to get abandoned with Agile is data integrity and documentation; Agile is just an excuse to scrap architecture and planning; Agile is just another word for developer laziness. Those are just some of the excuses that I have used recently. I have seen too many 'Agile' projects that have been abandoned after twenty or more three-week iterations when the final mess that was produced was unusable and a maintenance nightmare.

After reading Agile Analytics, however, I am beginning to understand what the author means by the difference between 'doing Agile' and 'being Agile'. Agile techniques, on their own, are not a replacement for Data Warehousing methodology, but rather a complement. On the other side of the Agile fence, I have been involved in several large projects utilizing the waterfall project management strategy that suffered from inevitable scope creep; missed deadlines; missed requirements; building throw-away products that will never provide value just to meet an arbitrary deadline.

The first section of Agile Analytics is geared more to a generalized audience in that it introduces the reader to the broad spectrum of Agile literature and how it applies to Data Warehousing. The second section is geared more to the Agile team members in that it provides them with the tools and frameworks for adjusting on a daily basis to the dynamism and challenges associated with Agile techniques.
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4 of 6 people found the following review helpful By Dallas Marks on January 19, 2012
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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2 of 3 people found the following review helpful By Methods & Tools Software Development Magazine on September 13, 2012
Format: Paperback
This book aims to provide an adaptation of the Agile development approach to the specific characteristics of Datawarehouse (DW) and Business Intelligence (BI) systems development. The book is well written and well structured. The concepts are illustrated with many anecdotes and examples. An important list of references and further reading material is available at the end of the book. My favorite part is the chapter 6 that deals with evolving design, a key factor for successful agile projects.

I will naturally recommend this book to every developer or manager involved DW and BI projects, but this book has also a much broader appeal. The issues specific DW or BI are not far for every large project, where databases play a major role, as it might be for instance in a mainframe environment. There you usually have to balance the architecture, performance and stability needs expressed on the database and operation sides of your organization with the goal of delivering frequently new working software. With his process of adapting Agile to data analytics, Ken Collier provides also a interesting framework for people that are involved in the transition from a traditional project management structure to an Agile approach.
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By JB on December 26, 2014
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.
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1 of 2 people found the following review helpful By Paul Kosinski on March 16, 2013
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.
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