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Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.

Businesses are consuming data at a staggering rate but when it comes to getting insights from this data they grapple with secure data access and data sharing, and ensure compliance. With new customer data privacy regulations like GDPR and the upcoming CCPA, the leash on data security policies is getting tighter, slowing down analytics and machine learning (ML) projects.

That’s why Databricks and Immuta have partnered to provide an end-to-end data governance solution with enterprise data security for analytics, data science and machine learning. This joint solution is centered around fine-grained security, secure data discovery and search that allows teams to securely share data and perform compliant analytics and ML on their data lakes.

Enabling Scalable Analytics and ML on Sensitive Data in Data Lakes

Immuta’s automated governance solution integrates natively with Databricks Unified Data Analytics Platform. The advanced, fine-grained data governance controls give users an end-to-end, easy way to manage access to Delta Lake and meet their organization’s security and data stewardship directives.

  1. Regulatory Compliance: Immuta offers fine-grained access control that provides row, column and cell-level access to data in Databricks. This makes it possible to make more data assets available to users without restricting entire table level access. All data security policies are enforced dynamically as users run their jobs in Databricks.
  2. Secure Data Sharing: By building a self-service data catalog, Immuta makes it easy to perform secure data discovery and search in Databricks. The integration comes with features like programmatic data access that automatically enables global and local policies on Spark jobs in Databricks. Data engineers and data scientists can securely subscribe to and collaborate on sensitive data while having the peace of mind for all their data security and privacy needs.
  3. Compliant Analytics and ML: Using anonymization and masking techniques in Immuta, Databricks users can perform compliant data analytics and ML in Delta tables within the context under which they need to act, e.g. vertical (HIPAA) or horizontal compliance (GDPR, CCPA). With automated policy application, the joint solution eliminates the need to check for permissions each time data is accessed to speed up analytics workloads while preserving the data value.

Get Started with the New Data Governance Tool

To learn more about the Databricks and Immuta partnership, check out the Data Governance and Data Security for Cloud Analytics webinar.

In this webinar, Steve Touw, Co-founder and Chief Technology Officer of Immuta, and Todd Greenstein, Product Manager at Databricks share details about the solution along with an in-depth demo of the native integration.

Additional Resources

Databricks Enterprise Security - Databricks

Security and Privacy — Databricks Documentation

Databricks and Immuta: Data Analytics with Automated Governance



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