Fast and Flexible: Exploring Agile Data Analytics
For the purpose of Cutter Consortium's latest CBR survey, we define Agile data analytics as "the application of Agile methods to data analytics initiatives in order to increase flexibility, provide faster 'time to value,' and support collaborative relationships between business users and IT developers." Further still, as described by Agile data analytics expert Ken Collier, Agile methods are built on a "simple set of sensible values and principles but require a high degree of discipline and rigor to properly execute" and as a process Agile falls somewhere in the "middle between just enough structure and just enough flexibility."1 For firms embracing Agile values and principles, which promote early and continuous delivery of business value throughout the development lifecycle, the primary objective of Agile data analytics is to deliver high-quality, high-value, working business intelligence (BI) solutions.
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