Chatting with your Analytical Data using OpenAI & LangChain
Presenting key highlights and limitations of different options to create a chatbot on analytical data, accompanied by insightful observations.
In a world where ChatGPT and other Large Language Models (LLMs) have set the industry abuzz, business and tech leaders are now setting their sights on using these powerful tools on their vast reservoirs of analytical data.
Analytical data typically boasts substantial volume; primarily comprises numeric data in structured formats; often contains company internal/confidential data and these frequently adheres to normalization standards. These distinctive characteristics, can present challenges to create a well-suited LLM-based chat application for analytical datasets.
In this blog post, I’ll show you few ways to create a chat application on a structured analytical dataset. We’ll discuss the pros and cons of each approach and ideas to overcome the challenges.
