Feature Discovery Integration with Snowflake Background

Feature Discovery Integration with Snowflake

Automatically build features from your Snowflake data.


Unleash the Power of Data Cloud with AI

Adopting AI across the organization has significant hurdles. DataRobot’s Feature Discovery streamlines this process by offering automated feature engineering that enables the creation of valuable new features for your machine learning models. This capability is integrated with Snowflake’s Data Cloud making feature generation more accurate, faster, and more cost-effective. Snowflake and DataRobot have invested time and resources into advancing the capabilities and benefits of one of the most critical tasks in AI — feature engineering.


The Best Features Fast

If you’re using Snowflake, chances are you have a lot of data to work with. That’s a great thing, but you still need to develop the right features for your models, and generate a single table with all of your data. DataRobot’s Automated Feature Discovery simplifies and accelerates this process through the automation of expert data science best practices.


Next-Generation Automated Feature Engineering

Compared to usual automated feature engineering solutions, Feature Discovery can leverage data from multiple tables, not just one. All you need to do is define how your tables are related to each other, and DataRobot automatically discovers, tests, and creates hundreds of valuable new features for your machine learning models, dramatically improving their accuracy.


Advanced Integration with Snowflake

Exploring multiple data sources has always required transferring large amounts of data between systems which was resource-intensive and time consuming. DataRobot’s new Snowflake integration pushes Feature Discovery operations into Snowflake to minimize data movement, resulting in faster results and lower operating costs.


Feature Discovery Meets Snowflake

We used the DataRobot Feature Discovery tool on our high-frequency physiological data, which helped us find some new features that ended up being high impact throughout all of our subsequent analysis.
Austin
Austin Chou

PhD, NIH Postdoctoral Fellow, Data Scientist UCSF Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center

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