Immuta provides Snowflake customers with advanced security, access-control, auditing and privacy management. Data-driven organizations that have moved to Snowflake can now add Immuta to store, analyze and share even the most sensitive data sets with ease.
Apply row-, column- and cell-level security using dynamic views to simplify role management.
Utilize a subscription-based Snowflake data catalog with always-on security and access control.
Discover and protect sensitive data for sharing across Snowflake.
“For any analysis on sensitive data [in Snowflake], we must protect the privacy of individuals by ensuring the data is appropriately anonymized. Immuta provides an intuitive interface to author complex anonymization policies with robust anonymization techniques such as dynamic k-anonymization, which enables the balancing of data utility vs. risk with minimal system complexity.”
– DARREN FUNG, CO-FOUNDER & CTO, DROP
Fine-Grained Access Control – natively in Snowflake
Controlling access to data within Snowflake can be complex, requiring copying sensitive tables, manual anonymization techniques or managing hundreds of user roles and secure views to define who can see what data. 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 — either across all data or on specific views. When users query data in Snowflake, Immuta policies are dynamically enforced to maximize both data security and utility.
Active Data Catalog for Snowflake
While the market is filled with offerings that claim to provide a unified data catalog, most do not enable true self-service, subscription-based access to live data due to the inherent security risks. Immuta’s active data catalog provides always-on policy enforcement that is explainable in plain english for full transparency. As a result, analysts can use Immuta to search, explore, understand policies and subscribe to Snowflake data sources. Because Immuta dynamically enforces access control policies on each Snowflake query, data engineering teams can confidently provide a live Snowflake data catalog without worrying about security or privacy risks.
Dynamic Data Masking
Data engineers today must ensure all analytics data and data use is compliant with a complex, growing set of regulatory and business rules. Immuta and Snowflake provide a dynamic approach to discovery, classification and protection of sensitive data for sharing on the Snowflake data marketplace, or internally, by using advanced math-based, auditable techniques for data masking, randomization and anonymization. Policies can be enforced dynamically for each user based on geography, duration of time, user subject attributes such as clearance level and more, without copying data or managing hundreds of roles.