Paul Butler, a self-described Data Hacker, recently published an article called “Make for Data Scientists“, which explored the challenges of managing data processing work. Paul went on to explain why GNU Make could be a viable tool for easing this pain. He also pointed out some limitations with Make, for example the assumption that all data is local.

We were gladdened to read Paul’s article, because we’d been hard at work building an internal tool to help manage our data workflows. A defining goal was to end up with a kind of “Make for data”, but targeted squarely at the problems of managing data workflow.