Michael Patterson

Most Databricks customers are driving a race car in second gear—access to 12+ products while actively using only 2-3. The problem isn't adoption; it's activation. This session reveals how one organization transformed from standard data engineering to full platform activation, lighting up a dozen products without platform migration. Through two parallel workstreams, we'll explore the journey from foundational data engineering to production-ready agentic AI. The first workstream demonstrates real-time Customer 360 integration, moving from batch reports to sub-100ms queryable APIs. The second showcases autonomous AI agents performing production work humans cannot do at scale—all governed by the same Unity Catalog managing traditional data assets. You'll learn the utilization gap framework, pattern-based approaches that replaced 20-30 weeks of bespoke engineering, and proof that the path from data engineering to agentic AI doesn't require buying more—it requires using what you own.