Enterprises can’t afford inconsistent governance. When analysts query the same data through Excel, Tableau, or an AI agent, the access controls, audit trails, and identity context must all hold, regardless of which tool made the request.
In this demo, see how AtScale’s semantic layer enforces governance at every layer of the stack: who can see which repositories, which data warehouses, and which deployed models, and how that user identity follows the query all the way to the data platform.
See how AtScale's semantic layer enforces governance across the entire stack: controlling access to repositories, warehouses, and deployed models, while carrying each user's identity straight through to the data platform.
What You’ll Learn
- How git-based repository controls limit which developers can see and modify which semantic models
- How data warehouse RBAC restricts which connections are visible to which users
- How deployed model permissions control what end users can query, including perspective-level access
- How AtScale impersonates the end user’s identity when passing queries to Databricks or Snowflake, enabling native platform audit trails
- Why “secure once, enforce everywhere” requires governance at the semantic layer, not just at the BI tool or the warehouse
