Role mining for Snowflake: four steps toward least privilege

In recent years, cloud data solutions like Snowflake have seen rapid adoption, but security and governance often lag behind. Many organizations still manage access to complex Snowflake implementations using traditional tools and processes from the on-prem era. This approach has limitations, leading to significant technical debt around identity security and access control in the Data Cloud. Access debt can manifest as high numbers of super-privileged users, bloated RBAC implementation, or deep role hierarchies that impact query performance. To address these issues, organizations should adopt best practices for managing access debt, such as flattening excessive hierarchies, defining and trimming super-roles and super-users, removing dormant users and unused roles, and establishing best practices for access requests. AI-based optimization capabilities can also help improve overall role structure in Snowflake.