"The Databricks lakehouse architecture represents a transformative approach to data management by seamlessly unifying the flexibility of data lakes with the reliability and performance of data warehouses. This convergence simplifies data governance by providing a single platform that supports both traditional OLAP workloads and modern AI/ML applications. Attendees will gain insights into how this architecture enables consistent data quality, robust security controls, and streamlined compliance processes, addressing the complex challenges organizations face in managing diverse data environments.

This session will also delve into best practices for implementing effective governance across the entire data lifecycle, including DataOps, MLOps, and ModelOps. By integrating governance into these operational workflows, organizations can ensure that data and models remain trustworthy, auditable, and compliant with regulatory requirements. Participants will leave equipped with practical strategies to leverage the lakehouse paradigm to drive innovation while maintaining control and transparency over their data assets."