Automating Data Insights: A Large Language Model-Driven Data Analysis Tool

Catherine Appleby Speaker
 
Monday, Aug 4: 10:35 AM - 11:00 AM
Invited Paper Session 
Music City Center 
Large language models (LLMs) are recognized for their confident assertions, particularly in mathematical contexts, which can occasionally lead to incorrect conclusions. To address this challenge and enhance the reliability of quantitative answers, we present an LLM agent to effectively answer analytical questions and interact with diverse datasets. This tool integrates an LLM with a code interpreter in a secure, sandboxed environment. The LLM generates code to effectively answer analytical questions, then the code is executed to provide accurate and reliable results.
To ensure confidence in the outputs, the tool provides the generated code, allowing users to verify the correctness of the calculations independently. Additionally, users can generate accompanying visualizations, to support findings and verify data insights. By combining LLMs with code execution capabilities, our LLM agent empowers users to quickly and reliably derive meaningful insights from their datasets.

Keywords

Large language model (LLM)

AI for Data Analysis