Automate Data Security and Privacy Controls With Immuta and Databricks
Why Immuta for Databricks?
Automate data security and privacy controls
Manage data security in sensitive environments with modern, fine-grained, attribute-based access controls (ABAC) dynamically enforced on jobs in Databricks.
Audit data access for compliance
Easily prove compliant data access with detailed audit logs and reports that show users’ data access levels, intended purposes, and query history — all in plain English.
Apply centralized policies to data science and analytics
Use local and global policies applied to workloads in Databricks for data science and analytics across R, Scala, Python and SQL.
How it works
Create access control policies
Author access control policies using a natural language policy builder
Enforce policies in Spark
Rules are natively enforced in Databricks and transparent to notebooks or analytics tools
Audit data use
Prove compliance in plain English using detailed audit logs at the data level
Use cases
Modernize access for Hadoop migration
Automate security and privacy controls when migrating from Hadoop, without the limitations of role-based access control.
Securely expand data access to more users
Provide more users access to Delta Lake with fine-grained access controls to manage row- and column-level security.
Access controls for data-as-a-service
Enforce access and privacy controls for each customer of your data product by dynamically enforcing rules natively in Spark without replicating data.
Summit session
“We picked Databricks and Immuta because they work well together. For us, the ability to deploy Immuta with Databricks in a couple of days for a proof of concept was a pretty big selling point.”
– Slava Frid, Platform Architect and CTO, WorldQuant Predictive
