Subject archive for "domino-product," page 4

The team at Domino is proud to be named a Visionary for the second year in a row in Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms. It is exciting to see that companies and industry analysts are increasingly realizing the value of a data science platform, and we’re honored to be recognized. It was particularly gratifying to hear feedback from our customers synthesized and channeled through Gartner’s report.

Randi R. Ludwig, Data Scientist at Dell EMC and an organizer of Women in Data Science ATX, covers how to build a Domino web app with Dash in this post.

This post is a recap of the common questions Domino answered in the booth at Strata New York. We answered questions about access to EC2 machines, managing environments, and model delivery.

We recently released new functionality that provides first-class integration between Domino and git. This post describes the new feature, and describes our perspective on the unique requirements of version control in the context of data science—as distinct from software engineering—workflows.

More than two years ago, we wrote about the misguided fear of the cloud among many enterprise companies. How quickly things change! Today, every enterprise we work with is either using the cloud or in the process of moving there. We work with companies that insisted, just two years ago, that they “can’t use the cloud” — and are now undertaking strategic initiatives to have “real work in AWS by the end of 2017.” We see this happening across industries including finance, insurance, pharmaceuticals, retail, and even government.

Managing “environments” (i.e., the set of packages, configuration, etc.) is a critical capability of any Data Science Platform. Not only does environment setup waste time on-boarding people, but configuration issues across environments can undermine reproducibility and collaboration, and can introduce delays when moving models from development to production.