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Domino 5.3 Unleashes Hybrid and Multi-Cloud Data Science at Scale

Domino 5.3 Unleashes Hybrid and Multi-Cloud Data Science at Scale
Major platform update increases speed and impact of enterprise data science with market-leading capabilities to unite hybrid and multi-cloud Infrastructure, democratize data sources and fuel deep learning.

Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced the availability of Domino 5.3, a major update that improves the time-to-value and impact of data science at scale across any cloud or on-premises infrastructure.

The latest platform version introduces a private preview of its Domino Nexus hybrid and multi-cloud capabilities, plus an expanded suite of connectors to simplify and democratize access to critical data sources, and new GPU inference capabilities that make it easier to productionize high value data science projects, including deep learning.

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Delivering on the vision for hybrid and multi-cloud MLOps

Industry estimates show that most AI infrastructure decision makers believe hybrid cloud support by AI platforms is important to their AI strategy. Domino initially announced its hybrid and multi-cloud architecture, Nexus, in June. Nexus helps enterprises protect data sovereignty, reduce compute spend, and future-proof their infrastructure investments across any cloud or on-premises infrastructure. Nexus is available to select Domino customers.

Domino Nexus delivers companies a single pane of glass for hybrid and multi-cloud MLOps.

“Organizations are stepping up their hybrid game, with 46% having some type of on-premises/off-premises architecture currently in place (up from 34% in 2019),” said Melanie Posey, research director for cloud & managed services transformation at S&P Global Market Intelligence. “Cost optimization across different workload deployment venues is one of the top use cases for hybrid.”

“Modern enterprise data science teams need access to a wide variety of data and infrastructure across different clouds, regions, on-premises clusters and databases,” said Nick Elprin, co-founder and CEO of Domino Data Lab. “Domino 5.3 gives our customers the ability to use the data and compute they need wherever it lives, so they can increase the speed and impact of data science without sacrificing security or cost efficiency.”

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Faster time-to-value with new data sources and GPU-backed model inference

Domino combines pre-built connectors to the most popular data sources, advanced search capabilities, and integrated data versioning, to maximize the productivity of data science teams. Domino 5.3 builds on the suite of data connectors introduced in prior releases with new capabilities to connect to Teradata warehouses, Amazon S3 tabular data and Trino.

Domino also offers the best environment for training advanced deep learning models at the cutting edge of AI and machine learning. New GPU-backed model inference capabilities in Domino 5.3 extend those advantages to model deployment, with no DevOps skills required. By operationalizing deep learning at enterprise scale, Domino enables the most critical workloads for the model-driven business.

Enabling compliant data science operations globally and by industry

Companies participating in the Nexus private preview can experience how it allows them to restrict access to data by region, helping to enforce compliance with data localization and sovereignty regulations. In addition, Domino 5.3 delivers new compliance and governance functionality for pharmaceutical companies that rely on Domino as a modern Statistical Computing Environment. An unalterable audit trail outlines who has been granted access to data within a project to comply with GxP guidelines for regulatory submissions for clinical trials.

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[To share your insights with us, please write to sghosh@martechseries.com]

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