Leveraging LLM for Business Intelligence
📰 Dev.to AI
Learn how to build a conversational BI agent using LLM to turn English questions into SQL and get insights from structured data
Action Steps
- Install Python 3.10 or newer to use the latest language features
- Install the OpenAI SDK using pip install to leverage LLM capabilities
- Build a conversational BI agent that turns plain English questions into SQL
- Run the SQL queries against a local SQLite database to retrieve relevant data
- Summarize the results for stakeholders using the conversational BI agent
Who Needs to Know This
Data analysts and product managers can benefit from this technique to simplify data insights and improve stakeholder communication
Key Insight
💡 Conversational BI agents can simplify data analysis and improve stakeholder communication using LLM
Share This
📊 Use LLM to turn English questions into SQL and get data insights without a complex semantic layer! 💡
Key Takeaways
Learn how to build a conversational BI agent using LLM to turn English questions into SQL and get insights from structured data
Full Article
We are building a conversational BI agent that turns plain English questions into SQL, runs them against a local SQLite database, and summarizes the results for stakeholders. This helps teams get insights from structured data without maintaining a complex semantic layer. I shipped a version of this for an internal ops dashboard, and the code below is exactly what I used. What you'll need Python 3.10 or newer The OpenAI SDK: pip install
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