di-agent-query-sql

To convert natural language to SQL, submit your data request to generate schema-verified queries involving filters, joins, and aggregations. The system applies Substrait-first planning and runtime dialect resolution to map queries to your specific source database dialect.

Substrait-first SQL generation handles unsupported expressions through resilient fallback processing. When compilation or conversion fails, it produces database-specific direct SQL generation and returns a concise warning instead of failing the entire operation.

Yes, you can generate SQL queries for different database dialects like PostgreSQL, Snowflake, and BigQuery. The system verifies project assets, resolves source connections, and maps them to the correct runtime SQL dialect during generation.

The best way to translate business questions into database queries without manual coding is using natural language data request conversion. Provide a grouped report or filtered metric query request to receive executable SQL mapped to your verified source tables.

Yes, schema-verified integration queries are required to generate SQL from natural language. The system verifies project assets and resolves source connections to ensure the generated SQL matches your database schema and runtime dialect correctly.

Natural language SQL queries fail during dialect conversion when Substrait compilation encounters unsupported expressions. The system recovers by falling back to direct database-specific SQL generation and providing a concise warning about the conversion issue.