Domino Lab partners with Snowflake for united MLops platform

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Machine-learning operations (MLops) management software maker Domino Data Lab has announced new capabilities in its Domino 5.2 platform designed specifically for use in Snowflake Data Lake, becoming a popular item in enterprise IT systems. The San Francisco-based company made the announcement on June 15 at the Snowflake Summit in Las Vegas.

Snowflake also announced Domino’s participation in the 2021 Series F fundraising round, with the aim of codifying new Domino-Snowflake product integration. Using the developer framework for Domino’s Platform and Snowpark, Snowflake, the two companies now offer an end-to-end enterprise data science lifecycle solution on a single data deployment platform, said Thomas, vice president of Domino’s partnership.

Working together for peace between developers and data scientists

Using Domino, Robinson said, data science teams can now more easily embed enterprise-wide model-driven applications in Snowflake’s data cloud.

“The partnership between Domino and Snowflake accelerates the MLops life cycle by automating non-data science tasks, eliminating solutions caused by clumsy tools and complex processes, and avoiding tensions between IT and data scientists,” Robinson said.

When software is being developed, conflicts often arise between developers and data scientists because sometimes they are at each other’s ends over whether the product is ready for release in a fast-fire devops environment.

Domino Data Lab claims that about 20% of its Enterprise MLops platform is used by Fortune 100. Using Domino, enterprises around the world can develop better drugs, grow more productive crops and build better cars, Robinson said.

What Domino brings into the partnership

With capabilities at every stage of the MLops lifecycle, Robinson said, this partnership strengthens Domino’s position as the most open and flexible enterprise MLops platform in the industry. Snowflake’s integration with Snowpark bridges the gap between data scientists, IT and business, allowing data engineers and data scientists to execute workloads directly on Snowflake as a common platform.

The new capabilities of Domino 5.2 include:

  • Rapid model development with secure, scalable access to data in Snowflake’s data cloud using Snowflake OAuth;
  • Flexible model deployment using Snowflake for in-database calculations, with modified deployment response times for critical applications by deploying models within the Snowflake Data Cloud and executing Python scoring code; And
  • To simplify model management by streamlining real-time model monitoring in Snowflake Data Cloud environments, with predictive data capture pipelines and monitoring, data drift and model quality detection for models deployed on Snowflake.

“Our focus is on three main things,” Robinson said. “We are for large enterprises that will often have regulatory or risk-related concerns with model development. Second, we are for code-first data scientists. And third, we are.” We often work with deep domain experts. “

Considering domain experts

Domino works well for people who go beyond drag-and-drop and actually use code, Robinson said.

“The platform is also designed for domain experts,” he said. “It may work for people who may not even have a title data scientist, such as one of our oil and gas customers, who is a drilling engineer. Our users often have a really deep understanding of their domains, they are better able to use data science, product development or functionality in that field. Our product is around those people. “

Influence with data science teams

Nick Alprin, CEO and co-founder of Domino Data Lab, said in a media advisory that data science teams have a wider impact by focusing on building progressive models and not worrying about data and infrastructure.

“Now, with this partnership, data scientists using Domino have Snowflake’s world-class data platform at their fingertips, making it much faster to model, deploy and monitor,” Alprin said.

Domino and Snowflake enable Aviation’s data science team to integrate seamlessly with person-generated health data and quickly prototype prototypes, all in a secure environment, said Audi’s lead data scientist Luka Foscini in a media advisory.

“They are integral to our work to measure health in everyday life, and ultimately turn data into strategies to promote good health outcomes,” Foschini said.

According to G2, Domino competes in a market segment that includes MATLAB, RStudio and RapidMiner.

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