Subject archive for "leaders-at-work," page 12

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.

Domino now offers data scientists a simple, yet incredibly powerful way to conduct quantitative work using Apache Spark.

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.

This talk took place at the Domino Data Science Pop-up in Austin, TX on April 13, 2016

For those wondering if data science platforms are really a thing, there’s a great article by Kevin Novak, the head of Uber’s Data Science Platform team. He describes the problems they saw with their data science team, and why they needed a platform.

Insights on process and culture from The Climate Corporation’s Erik Andrejko