Domino Data Lab Integrates with Snowflake To Help Mutual Customers Accelerate Returns On Data Science

Domino-Data-Lab-Deepens-Integration-with-Snowflake-to-Help-Mutual-Customers-Accelerate-Returns-on-Data-Science

Joint solution unites data scientists, business experts, and IT teams to accelerate data science

Domino Data Lab, a provider of the leading Enterprise MLOps platform trusted by over 20 per cent of the Fortune 100, announced at Snowflake Summit a partnership with Snowflake, the Data Cloud Company. This enhanced integration between its two platforms can pave the way for joint customers to rapidly evolve from data-driven businesses to predictive, model-driven businesses, and maximise returns on data science investments. 

A growing number of joint customers already use Domino data connectors to retrieve and write data between the Domino environment and Snowflake Data Cloud. Soon, they can use Snowflake’s Snowpark – a new developer experience – to build efficient and powerful pipelines in familiar constructs and using third-party libraries. From Domino, users can execute MLOps workflows in Snowflake to leverage the platform’s performance, near-infinite scalability, and near-zero maintenance, at a lower cost.

“To unleash the power of data science, companies must remove infrastructure barriers and enable data scientists to accelerate research and collaborate across the business,” said Nick Elprin, co-founder and CEO of Domino Data Lab. “We are thrilled to give data scientists enhanced access to Snowflake’s Data Cloud from our Enterprise MLOps platform.”

The enhanced integration will enable data scientists to easily leverage the data and processing power directly within Snowflake’s Data Cloud without sacrificing productivity and security to transfer data between platforms. Domino’s Enterprise MLOps platform provides self-service infrastructure so teams can develop and production models faster while IT can govern and manage data science infrastructure.

“Evidation’s platform enables anyone to participate in research and personalised health programs, and user privacy and control over permissions health data is foundational to why millions of individuals trust us,” says Luca Foschini, Co-founder and Chief Data Scientist at Evidation. “Snowflake provides the robust scalability, elasticity, and security we need to hold enterprise volumes of health data, while the integration with Domino ensures data scientists can securely and effectively share the model output with business stakeholders, clients, and partners.”

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With Snowpark, data scientists can leverage Snowflake’s powerful platform capabilities in languages using Java/Scala UDFs — leveraging its scalable processing and compute while running data science workloads directly where data resides. Model output remains in Snowflake for consumption by analytical applications or common reporting and BI tools for easy and secure collaboration without publishing model output back to Snowflake.

“By leveraging Domino and Snowflake’s Data Cloud together, Braze has the flexibility to build machine learning models across our databases and share data seamlessly across our organisation in real-time,” said Jon Hyman, co-founder and CTO at Braze, a comprehensive customer engagement platform. “With these improved data capabilities, we can better service our customers and help them deliver relevant and memorable experiences at scale.”

“Enabling data scientists to take advantage of Snowflake’s powerful platform capabilities will accelerate the adoption of data science and machine learning for decision making,” said Tarik Dwiek, Director, Technology Alliances at Snowflake. “With Domino’s streamlined integration, customers will be able to accelerate their journey towards modern model-based decision making.”