It goes without saying, in order to train data science models to produce predictive forecasts, you need data. But the process of getting the data into models is not always cut and dry, as data science and analytics teams continue to struggle with getting the right kind of data, in the proper format, for the appropriate analysis. As a result, teams end up spending more time uncovering and preparing data for data science models than they do on refining the actual models. But this doesn’t have to be the case.
Through the powerful combination of Snowflake and DataRobot, it’s now easy for data users to leverage the leading cloud data platform to quickly build, train and deploy data science models. Want to hear how?
Register today to hear from Josh Klaben-Finegold, Product Manager at Datarobot and Mike Klaczynski, Director of Product Marketing at Snowflake, as they discuss how you can conduct enterprise self-service data prep for data science in just a few clicks.