Session Details

Why a Data Lakehouse is the Best Approach for Scaling AI Workloads, Anywhere

Many organizations with data warehouses or data lakes are discovering that they are not prepared to scale AI workloads. A lack of processes and standards has led to a growing quagmire of unstructured, ungoverned data, best described as a “data swamp.” In this session, Paul Zikopoulos, Vice President of IBM Technology, will introduce you to a new approach using an open source, data lakehouse strategy, which can help resolve the problems hindering your ability to put analytics and AI to work at scale. Then, Tarun Chopra, Vice President of Product Management for Data and AI, will dive into IBM, a fit-for-purpose data store to scale AI workloads, and how leading companies are deploying it within their data strategy.

Additional Resources free trial

Try IBM for free where you can build, train, validate, tune and deploy AI models. free trial

In our free to start trial, you'll receive $1,500 to test drive an IBM open data lakehouse instance on IBM Cloud.

watsonx.governance demo

See watsonx.governance in action. In this 30 minute meeting, discover how you can use watsonx.governance.


Featured Keynote Speakers

Paul Zikopoulos

Paul Zikopoulos

Vice President, IBM Skills Vitality and Enablement, IBM

Tarun Chopra

Tarun Chopra

Vice President of Product Management for IBM Data and AI, IBM

Arakere Ramesh

Arakere Ramesh

Senior Director, Xeon Products & Solutions, Intel

Dan Gallivan

Dan Gallivan

Director, Worldwide Partner Solutions Architecture, Amazon

Brandon Beals

Brandon Beals

Director of Data and AI, Dot Foods


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