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?
The Need for a New Agile Framework When teams try to use an agile framework for data science, they often try to use Scrum, Kanban. Below I review the key challenges teams have in leveraging these frameworks have challenges. I also briefly explore a TDSP, which is newer framework already discussed on this web site. […]
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 […]
Do you think data science should be agile? When framing agility in the context of delivering usable insights frequently, iterating on these insights, and validating the outcomes, I think all of us would say “yes”. Yet, how do we achieve this? Even more basic, what does agile data science even mean? The article covers these […]