Domino Data Lab announces latest MLops platform to satisfy both data science and IT

At this morning’s keynote at the opening of Domino Data Lab’s Rev3 conference in New York City, CEO Nick Elprin announced the enterprise MLops leader’s latest platform, Domino 5.2.

The release, which will be generally available to customers in June 2022, includes 12 new capabilities to allow data science and IT teams to develop and deploy more models at a faster pace; reduce data and infrastructure complexity and costs; and extend autonomous model performance monitoring to Snowflake’s Data Cloud.


Playtime is over for data science, if companies can’t turn data science into business impact and describe that impact if work is still relegated to an AI innovation lab they are already behind, whether they realize it or not.”                                                                                                                                                                                                                                                                                                                  Nick Elprin CEO and Co-Founder of Domino Data Lab


Data science needs to work hand in glove with IT

Companies that are succeeding at data science, he continued, are doing the “hard, disciplined work to operationalize at scale, with model-driven businesses that go beyond data science to automate business processes and decision-making and weave data science and models into the fabric of the business.”

When speaking to customers, that three recurring themes tend to come up as key to model-driven business success. Companies need to hire data scientists and empower these experts; make it easy to find pathways to production; and provide cross-functional collaboration.


Data scientists need to work hand in glove with business and IT, Partnering with IT is especially important.”                                                                                                                                                                                                                                                                                                                                                               Nick Elprin CEO and Co-Founder of Domino Data Lab


The wrinkle, he continued, is that the more success a company has with data science, the more pressures there are to face and the harder it is to sustain that success. Increased data science use cases and applications create challenges for data science teams to be adequately empowered to meet the demands of the business.


One customer had early success with a deep learning NLP model and the business wanted them to scale the technology, but they were hamstrung with limited access to GPUs,”                                                                                                                                                                                                                          Nick Elprin CEO and Co-Founder of Domino Data Lab