What Stops Data Science from Scaling? Domino Data Lab to Host Enterprise MLOps Expert Virtual Panel on August 19th Exploring Common Failures and Solutions

Salesforce and CSL Behring Data Science Leaders Gather with Renown Thought Leader Tom Davenport for Roundtable Discussion

Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, will host a live virtual roundtable event on August 19 bringing together experts and veterans from across industries to discuss why most companies cannot succeed with data science at scale.

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Featuring live commentary and Q&A with thought leaders and experts leading AI and ML at some of the most sophisticated data-driven companies in the world, the roundtable discussion will provide IT and data science leaders with insight and proven real-world methods they can use to effectively scale data science.

97% of U.S. data executives say data science is crucial to maintain profitability and boost their company’s bottom line, according to a recent study commissioned by Domino Data Lab. However, nearly as many say that flawed approaches to data science strategy, execution and staffing make achieving that goal difficult. This event will offer attendees a glimpse into the most common challenges enterprises face, and share real-world examples of how the most sophisticated companies in the world are solving them with enterprise MLOps.

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Moderated by distinguished speaker, author, and advisor, Tom Davenport, one of Harvard Business Review’s most frequently published authors, the session will feature a panel of expert speakers including:

• Irina Malkova, VP of data science apps at Salesforce
• John K. Thompson, global head of advanced analytics & AI at CSL Behring
• Matt Aslett, research director for the data, AI & analytics Channel at 451 Research, a part of S&P Global Market Intelligence
• Nick Elprin, CEO and co-founder at Domino Data Lab

Throughout the open discussion, each speaker will bring their own point-of-view on implementing Enterprise MLOps practices into their operations. Attendees will also have an opportunity to ask the experts their opinions on best practices and the right processes they see work in practice to become a model-driven business.

“While companies have high expectations for data science and ML, their success requires deep changes across people, process and technology,” said Nick Elprin, CEO at Domino Data Lab. “This group of speakers brings together decades of experience running data science organizations at scale to power model-driven businesses. I’m excited to discuss how Enterprise MLOps is helping companies like CSL Behring and Salesforce weave data science into the fabric of their business.”

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