Data engineering is under pressure to support increasingly complex AI workflows—and fast. This panel dives into how leading teams are building robust, scalable infrastructure to power real-time AI applications. Experts will share hard-won lessons on pipeline design, data freshness, cost optimization, and tooling selection. Expect candid insights on where legacy architectures are breaking down, how vector and streaming solutions are evolving, and what’s actually working at scale.
