Agile analytics isn’t a novel concept in any shape or form. Things like feedback loops and process-oriented development seem to integrate flawlessly into the analytics paradigm, at least on paper. Heck, there’s even the Build-Measure-Learn framework for continuous development. It would be difficult to argue that analytics doesn’t have a role in something with measure in the name! However, past three years of working at Reaktor, one of the world’s top agile technology houses, have introduced me to a whole new set of problems with integrating an “analytics mindset” into an agile workflow, or an “agile mindset” into the analytics process.

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This year I had the opportunity to present at eMetrics London and Berlin on a topic that is very close to my heart. I’m psychotically neurotic about data quality. I’ve written about it many times before, and it’s pretty much why I want to keep on blogging and writing about analytics and tag management customizations. At eMetrics, I stepped out of my comfort zone of development and implementation, and chose to talk about organization practices.

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