Answer business questions without writing SQL every time
Business teams have questions. Data teams have the skills to answer them. But the queue of requests stretches weeks, and by the time an analyst delivers a report, the decision has already been made on gut instinct.
How the Analytics works
Stakeholders ask questions in plain English. The agent interprets the intent, maps it to your data schema, generates the appropriate SQL, executes the query, and returns a formatted answer. Complex questions still go to your data team, but the routine ones get handled instantly.
How it operates:
- Parses natural language questions and identifies relevant tables
- Generates optimized SQL for Snowflake, BigQuery, Redshift, or Postgres
- Returns results as tables, charts, or summary statistics based on question type
- Logs all queries for governance and auditing
Why you need the Analytics
You need a documented schema and a data warehouse in place. The agent does not build your data infrastructure. It sits on top of what you already have and makes it accessible to people who cannot write SQL.
Analytics vs. Data Science
The Data Science Agent supports model building, experiment tracking, and feature engineering. The Analytics Agent handles reporting and ad-hoc analysis. If your team builds models, use the Data Science Agent. If your team answers business questions, start here.
