Agile has taken the software community by storm with Scrum and Kanban leading the way. What are these approaches and do the fit in the world of data science?
Scrum is an agile collaboration framework that can help teams increase the agility of their data science projects. Co-founded by Jeff Sutherland and Ken Schwaber in the 1990s, Scrum has become the most commonly used agile approach with over 12 million practitioners (scrum.org). Although heavily adopted in software, Scrum is also used across a wide variety […]
There are three key concepts that should be followed within an agile data science effort – use iterations, keep the iteration as small as possible and get feedback on each iteration. In other words, while there are several alternative data science workflow frameworks (sometimes known as data science life cycle frameworks), to achieve agility, agile teams should execute an […]