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Snowflake Announces New Features to Bring Together the World’s Data in the Data Cloud

unveiled its latest product innovations that redefine what’s possible in the Data Cloud. At its annual Snowflake Summit, the company announced innovations in data programmability, global data governance, and platform optimizations to empower organizations to bring more data together in the Data Cloud, achieving deeper value from data and powerful business insights.

Data programmability innovations:

  • Snowpark. With initial support for Java and Scala, Snowflake’s developer experience, Snowpark, allows data engineers, data scientists, and developers to build using their preferred language and familiar programming concepts, and then execute these workloads directly within Snowflake. Currently in private preview, with public preview coming soon.
  • Java UDFs. With Java user-defined-functions (UDFs), customers can bring their custom code and business logic to Snowflake for better performance and expanded use case capabilities, all while reducing management complexity. Currently in private preview, with public preview coming soon.
  • Unstructured data. Snowflake is bringing accelerated time-to-value to unstructured data, enabling customers to store, govern, process, and share file data alongside their structured and semi-structured data and unlock new revenue opportunities. In private preview, with public preview coming soon.
  • SQL API. The Snowflake SQL API enables custom and off-the-shelf applications to call Snowflake directly through a REST API, without the need for client-side drivers, thus reducing the complexity and administration overhead requirements. In public preview.

Snowflake customers like Sainsbury’s are already leveraging Snowflake’s data programmability capabilities.“Snowflake enables us with a flexible, scalable toolset and processing power to bring together granular data and build upon the data we already have,” Sainsbury’s Senior Data Viz and Automation Manager, Steven Henson-Tyers said. “With Snowflake’s Data Cloud, our data scientists have more access to the near real-time information needed to build and iterate on models more quickly and effectively.”

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