Data science and machine learning (ML) are revolutionizing how organizations make business and product decisions, and how they retain and attract new customers.
But data science isn’t easy. It requires fast access to all of an organization's data, powerful data engineering capabilities, and support for an ever-expanding ecosystem of ML tools, frameworks, and libraries.
In this session, Snowflake product leaders will demonstrate how Snowflake streamlines the data science process by:

Managing all types of data for ML
Enabling data pipelines with custom code beyond SQL
Operationalizing ML
Orchestrating data science resources outside of Snowflake
Integrating directly with data science partners
(external functions, Java UDF, Unstructured data management)