Description
For data teams, migrating new workloads into Databricks - whether from Hadoop platforms, cloud computer layers, or on-premises databases - is a significant undertaking. A critical step in migrating workloads, especially sensitive data, is to provision access controls that enable compliance with internal rules or privacy regulations such as GDPR, CCPA, or HIPAA. This session will explore various Databricks access control scenarios -- such as credential passthrough, table ACLs, and partner solutions -- to automate security and privacy controls on sensitive data. For each scenario, automation strategies will cover managing user access, enforcing data policies, implementing privacy-enhancing technologies, and data movement. A case study will be presented to put these concepts in practice, including lessons learned at a Fortune 500 company undergoing a complex, on-premises migration to Databricks Delta Lake to unify their data analytics while complying with internal rules and privacy laws such as CCPA. About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: …
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