Protegrity, a leader in data-centric security, today announced that it has become a validated Databricks partner to help enterprises accelerate AI and analytics on governed, secured data.
As a Validated Databricks Partner, Protegrity has completed Databricks technical validation for its integration with Databricks Unity Catalog, Standard & DB SQL computes. This validation confirms that the Protegrity integration meets Databricks standards for quality, security, and interoperability, and aligns with Unity Catalog governance requirements. The validated integration enables customers to protect sensitive data using Protegrity’s data protection capabilities while securely accessing Unity Catalog–governed data for analytics and AI on the Databricks platform.
Working Together, Protegrity and Databricks Help Organizations Secure Sensitive Data While Accelerating AI Innovation
The Protegrity Platform integrates with Unity Catalog to help organizations apply consistent, fine-grained data protection controls—such as tokenization, encryption, and dynamic data masking—across governed lakehouse assets. This integration is designed to support enterprises as they operationalize AI and analytics while meeting security, privacy, and regulatory requirements.
Through technical alignment with Unity Catalog, Protegrity helps ensure that sensitive data remains protected throughout its lifecycle, from ingestion and analytics to AI and machine learning workflows. Organizations can confidently enable broader data access for analytics and AI while maintaining centralized governance and strong security controls.
Key Benefits of the Protegrity and Databricks Integration Include:
Data Protection by design for AI and Analytics
Protegrity enables protection of sensitive data used by analytics, BI, and AI workloads running on Databricks, helping organizations reduce risk while expanding data access.
Fine-grained, policy-based controls
Integration with Databricks Unity Catalog allows organizations to align data protection policies with centralized governance, helping ensure consistent enforcement across users, workloads, and tools.
Support for AI with guardrails
AI and advanced analytics workloads can operate on protected data, helping organizations enable use cases such as retrieval augmented generation (RAG) and advanced analytics while limiting exposure of- sensitive information.
Reduced compliance and security risk
By protecting sensitive data at scale, organizations can help meet regulatory and privacy obligations without slowing innovation or increasing operational complexity.
Hybrid and multi-cloud readiness
Protegrity supports data protection across hybrid and multi-cloud environments, helping organizations maintain- consistent controls as data moves across platforms and use cases.
“Organizations want to move fast with AI, but not at the expense of security or privacy,” said Saravana Krishnamurthy, Senior Vice President, Product Management. “Our integration with Databricks Unity Catalog helps customers protect sensitive data while enabling trusted analytics and AI at scale.”
This collaboration underscores Protegrity’s commitment to helping enterprises modernize their data architectures with security and privacy built in, enabling trusted data access for analytics and AI across the Databricks ecosystem.
To learn more about Protegrity’s data protection capabilities and how Protegrity works with Databricks, visit here.