Exasol Labs

You can create, import, and maintain Exasol Semantic Views models, derive metrics from physical tables and query logs, author fact and dimension entities with SQL-native metric DDL, review models for approval handoffs, and query published models through semantic SQL and the Exasol MCP Server.

They target data engineers, domain owners, and analytics engineers working with Exasol Semantic Views. The modeler skill serves model authors, the reviewer skill supports governance and approval stakeholders, and the analyst skill serves consumers querying published semantic models.

The modeler creates and validates the semantic model, the reviewer assesses scope, evidence, and diffs to coordinate human approval gates before publication, and the analyst queries the published model. Together they cover the full lifecycle from modeling through governance to consumption.

The analyst skill assumes an Exasol Semantic Views model is already published. It leverages comment-aware semantic discovery, metric and dimension descriptions, and compatibility checking, and can operate through the official Exasol MCP Server for structured request compilation and result execution.

Yes. The exasol-semantic-modeler skill explicitly covers Databricks UCMV import, alongside schema and catalog-comment inspection, historical query-log analysis, and autonomous metric derivation from physical tables to bootstrap or maintain a semantic model.