Subject archive for "knowledge-management"

Data scientists often greet the topic of knowledge management with a sense of dread. Some see it as a time-sucking distraction from their “real” jobs; others don’t fully grasp what it means. Even many who see the concept’s value find the process painful.

As more companies recognize the need for a [data science platform], more vendors are claiming they have one. Increasingly, we see companies describing their product as a “data science platform” without describing the features that make platforms so valuable. So we wanted to share our vision for the core capabilities a platform should have in order for it to be valuable to data science teams.

This morning there was a great conversation on Twitter, kicked off by Hadley Wickham, about one of the ugly little bits of the data science process.

We’re excited to announce a set of big new features that make it easier for you to find and reuse past data science work in your team and organization. We’re calling these features “Discoverability,” and they encompass powerful ways to search, tag, and get recommendations about relevant analytical work.