Keynote Data Session: 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 watsonx.data, a fit-for-purpose data store to scale AI workloads, anywhere, and how leading companies are already seeing success.

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

Arakere Ramesh,  Senior Director, Xeon Products & Solutions, Intel

Paul Zikopoulos, Vice President, IBM Skills Vitality and Enablement, IBM

Dan Gallivan, Director, Worldwide Partner Solutions Architecture, Amazon
Brandon Beals, Director of Data & AI, Dot Foods, Inc.

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