How Data Warehousing Changes in the World of Agents

The rise of agentic applications is reshaping what we demand from data warehouses. Agents don't operate on yesterday's batch — they require fresh, consistent data with sub-second latency to reason, decide, and act in real time. In this session, we examine why traditional data warehousing patterns, built around scheduled ETL and human-speed concurrency and latency, fall short when the consumer of your data is an army of agents making thousands of decisions per minute. We address the challenges this shift introduces: tighter freshness SLAs, evolving governance when agents —not people — query your data, and the complexity of always-on pipelines. We then explore how real-time lakehouse capabilities — streaming ingestion, incremental materialization, high concurrency and low-latency query serving, and unified governance — support agentic applications at scale. This session offers a framework to make your lakehouse real-time and agent-ready.