Unity Catalog Lakeguard - Data Governance for Multi-User Apache Spark Clusters
Databricks via YouTube
Overview
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Explore how Databricks enables efficient multi-workload execution on a lakehouse platform while maintaining robust data governance in this 26-minute presentation. Discover the innovative features of Shared Clusters and Unity Catalog, which allow users to run diverse workloads from analytics to machine learning using SQL, Python, or Scala. Learn how these Databricks-exclusive capabilities reduce costs, minimize operational overhead, and enable secure execution of all workloads on shared compute resources. Presented by Martin Grund, Principal Engineer, and Stefania Leone, Director of Product Management at Databricks, this talk demonstrates how organizations can achieve cost-effective and secure data management without compromising on functionality or performance.
Syllabus
Unity Catalog Lakeguard: Data Governance for Multi-User Apacheâ„¢ Spark Clusters
Taught by
Databricks