Agile Analytics

The goal of this book is 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 divided into two parts. The first focuses on Agile project management techniques and delivery team coordination. The second part focuses on the technical methods that are necessary to enable continuous delivery of software.

I will naturally recommend this well written book to every developer or manager involved DW and BI projects, but this book has also a much broader appeal. The issues specific data analytics 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.

Reference: Agile Analytics, Ken Collier, Addison-Wesley, 314 pages, IBSN 978-0-321-50481-4


In Coaching Agile Teams, Lyssa Adkins differentiates cooperation from collaboration, explaining that group cooperation yields the sum of its parts, while collaboration yields a sum that is greater than its parts (Adkins 2010). Cooperation between group members involves the smooth transfer of work in progress, work products, and information from one member to another. The team has a shared commitment to a common outcome, and individuals coordinate their activities in ways that support other group members. In a cooperative team, members interact in an egoless manner and understand their individual roles as they relate to the group’s objectives.

Agile Analytics presents a difficult paradox: The ability to quickly respond to change and frequently deliver new features requires excellent data models and system design, yet excellent design takes time to develop. How do we deliver business value early and frequently without doing a lot of the design up front?

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