Agile for Data - Introduction
In the 8+ years I’ve worked with data, I have yet to see an analytics team effectively deliver a data project using the agile methodology seen in the application/software space. For the past year and a half, I have been on a journey to change that.
The long-term goal of this series is provide a repository of information around the best-practices for leading and organizing data-related projects using Agile principles.
The goal is not to teach you Agile, but rather how to leverage one’s experience with agile in the context of a analytics initiative.
Data projects are nuanced from their application/software counterparts, and thus require additional customization of traditional agile practices to make them successful.
In addition, most data teams in industry are NOT using traditional agile, and thus this institutional reluctance to change further impacts the ability to delivery with agility.
Consider a Cake…
A cake illustrates the analytics technology we work with:
Staging (or Raw) Layer
Do you eat a cake by slicing it horizontally?
Why do we structure our work in such a manner?
We are not laying bricks. We are eating cake.
Welcome aboard the journey!