Integrations

Data Governance for Databricks

Protect your Databricks environment from exposure, leakage, and misconfiguration.

The Challenge

Databricks delivers a unified analytics and AI platform that enables massive data processing, collaborative development, and deployment of machine learning and generative AI applications. But this level of flexibility introduces specific security risks, including misconfigured access controls on shared clusters, exposed credentials and tokens in notebooks, and insufficient auditing of data access and movement.

Misconfigured permissions and exposed credentials can lead to unauthorized access or large‑scale data exfiltration.

Solution

Strengthen Databricks security by using AI to classify, monitor, and protect sensitive data.

Semantic Intelligence™ identifies risky activity across notebooks, jobs, and data assets. It detects unauthorized access attempts, credential exposure, and configuration gaps so security teams can take action in real‑time.

Sensitive data in notebooks

Code, queries, and documentation in Databricks notebooks often contain credentials, PII, or sensitive logic that can be inadvertently shared or exposed. Semantic Intelligence scans data and flags sensitive information stored in notebooks to help teams remediate risk before it results in a breach.

Unauthorized access and exfiltration detection

Without continuous monitoring and granular auditing, unauthorized data access and exfiltration can go unnoticed across Databricks workspaces and clusters. Semantic Intelligence provides visibility into access patterns and teams get real‑time alerts for suspicious activity.