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The slides are available to download below and please share any of your questions here.SummaryWhen storing and making use of data for analytics and AI, most enterprises have multiple data warehouses and data lakes, on-prem and in cloud. Warehouses offer expensive, high-performance solutions for structured data, and lakes offer cheaper solutions for big, unstructured data.Built on an open lakehouse architecture, watsonx.data is the only open, hybrid, and governed data store optimized for all data, analytics and AI workloads.Learn how watsonx.data allows you to:
Key SpeakersKevin Shen - Product Manager, watsonx.data, IBM Data & AIKevin works as a product manager at IBM, where he leads the watsonx.data product roadmap. He is interested in the evolution of data warehousing and lake products, especially for advanced analytics and AI. He is excited to solve complex problems in an ambiguous environment and enjoys bringing ideas to reality with a diverse and innovative team.Mathieu Dumoulin - Senior Expert, McKinseyMathieu leads data and analytics transformation programs in banking and other industries (e.g., insurance, mining, healthcare), with a holistic, deep understanding of data strategy, org (e.g., CDO, roles & responsibilities, recruiting), data governance, data architecture and security. He has successfully led as top expert in data management for large programs to successful delivery*When comparing published 2023 list prices normalized for VPC hours of watsonx.data to several major cloud data warehouse vendors. Savings may vary depending on configurations, workloads and vendor.