Google BigQuery Data Governance

Immuta provides Google BigQuery customers with advanced security, access-control, auditing and privacy management. Data-driven organizations that have moved to Google BigQuery can now add Immuta to easily store, analyze and share even the most sensitive data sets.

Fine-Grained
Access Control

Apply dynamic row-level security, column-level security and cell-level protection.

Centralized Access
Control and Data Security

Reduce risk with consistent access control across GCP and non-GCP database services.

Dynamic
Data Masking

Discover and protect sensitive data for use.

SECURITY

Fine-Grained Access Control

Controlling access to data within Google BigQuery can be complex, requiring DDL operations to grant access to specific columns for hundreds of roles or creating views for row-level filtering on a table to define data access. With Immuta, you can streamline access control by automatically governing who can see and use what data. Data engineers use Immuta to create modern, fine-grained access control policies — across all data. When users query data from Google BigQuery, Immuta policies are dynamically enforced to simplify role management.

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CONTROL

Centralized Access Control and Data Security

The market is filled with data catalog offerings to centralize access, but most don’t enable enforcement on access control and data security policies across Google BigQuery and other data sources. Immuta provides consistent data classification and dynamic policy enforcement across GCP’s cloud database services, including GCP DataProc and GCP Cloud SQL databases, as well as those on other clouds like Snowflake or Databricks. Data engineers can simplify management and reduce risk across the cloud data platforms.

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MASKING

Dynamic Data Masking

Data engineers must ensure analytics data and data use are compliant with complex, growing sets of regulatory and business rules. Immuta and Google BigQuery provide a dynamic approach to sensitive data classification, discovery and protection using advanced math-based data masking, randomization and anonymization techniques that are fully auditable. Policies can be enforced dynamically based on geography, time duration, user attributes such as clearance level and more, without copying data or managing hundreds of roles.

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