It might seem like a Big Data or Machine Learning project wouldn’t lend itself to an agile software development approach. The “Big” in Big Data implies lots of infrastructure and up front work in order to get things moving before a single piece of useful user functionality can be delivered.
In fact the very experimental nature and huge unknowns implicit in almost all of these projects makes an agile approach very well suited.
Ade Miller has spent the last four years working on Big Data and Machine Learning projects, first at CenturyLink Cloud and more recently at Conga.
He shares the results of his experiences successfully delivering big data and machine learning with agile. In addition to talking about his experiences, what worked and what didn’t, he also discusses how to adjust your agile approach to take into account the unique constraints of these types of project.