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Dataiku Introduces Integration With Snowflake To Enable Support For Advanced Data Functions

Dataiku Introduces Integration With Snowflake To Enable Support For Advanced Data Functions

Dataiku Also Announces Participation In Snowpark, A New Developer Experience From Snowflake

Dataiku, the world’s most advanced Enterprise AI platform, announced an integration with Snowflake’s Snowpark and Java user defined functions (UDFs), a new developer experience for Snowflake, following the announcement of both at Snowflake Summit. By adding support for Java user defined functions (UDFs) now supported by Snowflake, Dataiku continues to lead in push down computation; with Snowpark, Snowflake and Dataiku will enable data engineers, data scientists, and developers who prefer other languages to take advantage of Snowflake’s powerful platform capabilities and the benefits of Snowflake’s Data Cloud.

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“Snowflake is known for its performance, scalability, and concurrency. Before Snowpark and Java UDFs, interaction with Snowflake was mostly through SQL”

With the Java UDF integration, Dataiku users can now take better advantage of Snowflake for more operations visual data preparation users can now push down the computation of more visual recipes to the Snowflake engine, and scoring can also take place directly in Snowflake. Both areas can then take advantage of the elastic scale of Snowflake, so organizations can operate on larger datasets, work faster, and only pay for what they need. Pushdown also minimizes data movement so data stays in Snowflake, which enhances data security and relieves compliance concerns. With Snowpark, users will also see an increase in functionality and more access for developers — so that more developers in the enterprise can build services to interact with Snowflake services, while making the most of Dataiku’s platform for advanced analytics at scale.

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“Dataiku was designed to natively leverage the compute power of data platforms. The release of Snowflake’s Snowpark & Java UDFs allows us to expand our existing pushdown support from SQL to more advanced functions in both data preparation and predictive scoring directly in Snowflake. This gives our users the ability to optimize the processing of their AI applications in Snowflake,” said JC Raveneau, Senior Director, Product Management at Dataiku.

“Snowflake is known for its performance, scalability, and concurrency. Before Snowpark and Java UDFs, interaction with Snowflake was mostly through SQL,” said Isaac Kunen, Senior Product Manager at Snowflake. “These features enable customers to create and manage more workflows entirely within Snowflake’s Data Cloud, without the need for additional processing systems — advancing Snowflake’s mission to mobilize the world’s data, and giving more users the ability to achieve powerful data insights with Snowflake’s Data Cloud. Partnering with Dataiku, a company that shares this vision to democratize data insights, will benefit joint customers with accessible and integrated analytics solutions.”

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