Suchith Nair

Highly regulated organizations struggle to balance data democratization with governance, operational overhead, and tool sprawl. In this session, we share how we scaled a Databricks-centered platform using a governed multi-tenant model that separates interactive self-service analytics from production-grade data services. We outline the architecture and operating patterns that enabled growth—governance, tenancy, and automated deployments—and how we implemented Lakeflow, including Lakeflow Connect, to standardize ingestion and consolidate third-party tools into Databricks-native services. Attendees will gain practical strategies to define workload boundaries, enable repeatable low-risk deployments, operationalize ingestion as a product, and execute phased consolidation with measurable outcomes.