Vanna: Your AI Business Intelligence Assistant Frequently Asked Questions

Vanna: Your AI Business Intelligence Assistant Frequently Asked Questions. Vanna: Your AI Business Intelligence Assistant: This ai tool generates SQL for Snowflake, BigQuery, Athena, Postgres—empowering data teams with instant query creation.

FAQ from Vanna: Your AI Business Intelligence Assistant

What is Vanna: Your AI Business Intelligence Assistant?

Vanna is an open-source, AI-powered assistant that converts natural language into accurate SQL queries. It's built to accelerate data analysis across modern cloud data platforms using customizable machine learning models.

How to use Vanna: Your AI Business Intelligence Assistant?

Install the Vanna Python library, authenticate with your chosen LLM provider, connect your database schema, and begin asking questions. The 'ask()' function returns ready-to-run SQL based on your context and history.

What databases does Vanna support?

Vanna natively supports Snowflake, BigQuery, Athena, and Postgres, but its modular design allows integration with virtually any SQL-based database through proper configuration.

How does Vanna ensure high accuracy in SQL generation?

Accuracy is driven by targeted training on your schema, sample queries, and feedback loops. The more domain-specific training data provided, the better Vanna understands your data landscape.

Can I use Vanna with my own database and schema?

Absolutely. Vanna is designed to be trained on your private database schema and query patterns, ensuring personalized and secure SQL generation without exposing sensitive structures.

Does Vanna continuously improve over time?

Yes. As you interact with Vanna and validate outputs, it retains knowledge from past successes and adjustments, enabling smarter responses with continued use.

What are some practical applications of Vanna?

Use Vanna to automate report generation, empower non-technical users to explore data, reduce SQL drafting time for engineers, build intelligent chatbots for analytics, or integrate SQL capabilities into SaaS products.