Chat Examples
See how users chat with the AI assistant and how they use the MCP server.
A data analyst investigates why a revenue dashboard shows incorrect numbers by tracing upstream data quality failures via root cause analysis.
A governance lead sets up a PII classification with nested tags and applies a sensitive tag to a customer table column.
A data engineer adds data quality tests (not-null and value range) to a key column on an orders table.
A new analyst explores customer churn datasets using semantic search and reviews the most relevant table's details.
A data product owner establishes a Finance domain, creates a Revenue data product within it, and registers a daily revenue metric.