Deloitte: Talking MLOps in the Enterprise

We sat down with Subhadip Roy, Head of Machine Learning Engineering, AI, & Data at Deloitte, to talk MLOps. What people and teams are getting right with MLOps? What they are getting wrong? What is the impact of MLOps (when implemented correctly)? And how Dataiku can help make MLOps a success?
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"From building that model, validating that model, then putting it into production — the turnaround time was about 6-8 weeks. ... That's where we combine with platforms like Dataiku to build a system where you can deploy the models in days, not weeks. Making sure the algorithms you have in production are picking up the latest trends." Subhadip Roy Head of Machine Learning Engineering, AI, and Data at Deloitte

MLOps With Dataiku


Mount Sinai: An Enterprise Data Blueprint for Success

Mount Sinai has pivoted its processes to create more holistic methods which enable lasting results and life-long, positive impacts in patients’ lives. At the core of this transformation? Dataiku.

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Pfizer: Everyday AI Is A Journey,
Not A Destination

Debbie Reynolds, VP Enterprise Data Solutions and Engineering at Pfizer, discusses how the company has been able to put data at the core of everyday business decisions.

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Oshkosh: Shifting Gears From Traditional to Data-Driven Manufacturing

Learn about the culture of data science at scale that Oshkosh Corporation has developed using modern software tools like Dataiku — a culture that has enabled significant cost savings and performance improvements over a variety of solutions for the business and their customers.

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Standard Chartered Bank: Driving Business Outcomes With Data

Across all areas of the bank, Standard Chartered is accelerating the development of AI solutions, creating a culture of decision making driven by analytics and unlocking the value of data to power better business outcomes.

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