Conversational analytics with dbt

Описание: Teams across analytics, finance, marketing, and product are using conversational interfaces to safely access and chat with governed data. They can:
Run quick, safe analysis: “Average order value by region?”
Ask clarifying definitions: “What does ‘qualified lead’ mean?”
Trace lineage: “What feeds into `monthly_churn_rate`?”
Investigate anomalies: “Did any upstream sources change before this spike?”
Find models: “Is there a model for trial-to-paid conversion?”

If you're thinking about conversational analytics, start with dbt as your foundation.

Ask yourself:
Is your data structured and governed?
Are metrics defined, tested, and version-controlled?
Can AI access lineage and documentation to explain results?
Is access properly governed and cost-efficient?

With dbt, you can connect any LLM (Claude, OpenAI, or your own internal assistant) and build your own multi-step conversational analytics agents via the dbt MCP server: https://docs.getdbt.com/docs/dbt-ai/a....

Or try the dbt Analyst Agent (now in beta), a purpose-built AI agent that reasons directly on your governed data: https://www.getdbt.com/product/dbt-ag...

It’s time to unlock the structured data and metadata your team already trusts. Get a demo of the dbt MCP server today: https://www.getdbt.com/contact

Or join the dbt Agents waitlist: https://www.getdbt.com/product/dbt-agent