Training data science models to produce predictive forecasts requires data. But the process of getting learning data into models is not always cut and dry; 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 easy for data users to quickly build, train, and deploy data science models. During this webinar, Josh Klaben-Finegold (Product Manager at DataRobot) and Mike Klaczynski (Director of Product Marketing at Snowflake) will share:
Approaches to conducting enterprise self-service data prep for data science in just a few clicks.
How Snowflake + DataRobot empower users to collaborate, prepare, and process data for machine learning at scale, with enterprise governance.
Tips for easily preparing your data for feature engineering.
A live demo of the power that Snowflake + DataRobot offer.