Subject archive for "data-science-teams"

With our Fall 2023 release, a significant productivity boost is added to Domino by integrating Jupyter AI into Domino Workspaces.

How do you build a data science capability into a powerful force for making decisions about virtually all facets of your business? And how do you recruit, train, organize, and retrain members of your team, in a field where competition for talent is intense and growing? These are just a couple of the questions that Glenn Hofmann, chief analytics officer at New York Life Insurance Company, has confronted and mastered in his tenure there.

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant.

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. We’re introducing groundbreaking new features – including On-demand Spark clusters, enhanced project management, and the ability to export models – that give enterprises unprecedented power to scale their data science capabilities by addressing common struggles.

Last week we announced that Domino is now fully Kubernetes native.