Further, to protect sensitive data, Securiti provides data governance teams the ability to automate dynamic data-masking policies. Inside an organization, various teams use Snowflake for projects such as moving data in/out, running models, business reporting, analytics, etc. Depending on the project, users may not need to access sensitive data stored in tables. For example, a financial analyst working for a bank may not need access to SSNs, but only transaction amounts. Based on patterns of data breaches, we know that over-provisioned access often leads to data privacy and security breaches such as data used for non-approved purposes. To address this concern, the data governance team can create a view each time it needs to grant access to a subset of a table. However, this is not scalable as the number of views can grow large and become unmanageable. With Securiti, customers can leverage Snowflake’s built-in dynamic data masking capabilities to enforce fine-grained policies to protect sensitive data that ensure data isn’t exposed to any unauthorized use.
Finally, Securiti can harden the Snowflake environment by continuously monitoring for data risk and security posture settings in Snowflake, so organizations can safely share and collaborate with their data in a secure manner.
Besides Snowflake, Securiti provides native integration with 250+ on-premise, multi-cloud, and SaaS data systems. Using these integrations, organizations can easily discover sensitive and personal data stored in their data systems and streamline their data governance, security, and privacy functions in a single platform. With these capabilities in place, Securiti can help organizations mitigate risk of data breaches, protect individual privacy rights, and address global data regulations such as NIST, PCI, GDPR, and CCPA.