AtScale is the leading semantic layer solution for modern business intelligence and data science teams. AtScale insulates data consumers from the complexity of raw data, exposing a business-oriented data model and virtualizing queries that leverage the capabilities of powerful cloud data platforms like Synapse, Databricks, and Snowflake. BI teams connect to AtScale with common data visualization tools including Power BI, Excel, Tableau, or Looker.  Data scientists access the semantic layer with python to consume a common view of enterprise metrics and dimensions with Auto ML platforms like DataRobot and Jupyter. 

AtScale customers leverage an intuitive modeling environment to define a business-oriented data model on raw cloud data. Once published, an AtScale model establishes a single source of key metrics and dimensions for all data consumers to leverage. 

Users access live cloud data through AtScale with no ETL or physical data movement. AtScale delivers the dimensional data analysis capability and query performance of traditional OLAP tools with no limitations on the size or physical location of underlying data.  AtScale presents a virtualized view of data within the semantic model to visualization platforms and coordinates query execution on the cloud data platform. Leveraging connections optimized for BI clients (including native DAX for PowerBI), automation integrated with cloud data platforms, and AI powered orchestration, users get unparalleled query performance on live cloud data.

The AtScale semantic layer supports self-service BI and data literacy initiatives by simplifying the enterprise data model and making analytics more reusable and discoverable. Data science teams minimize time spent with data prep and are able to leverage the semantic layer to simplify feature engineering. Analytics governance and security policies can also be enforced at the semantic layer.