Developing an AI based Business Data Analyst using OpenAI Function Calling || Bernhard Schäfer

Key insights 🧠 Developing an AI-based business data analyst using open AI function calling can potentially challenge the role of traditional data analysts. 🧩 The AI-based business data analyst was able to load and inspect the CSV data, generate Python code, and create a chart, showcasing its potential in automating data analysis tasks. 🤷‍ “Overall, I’m not very concerned“ - Despite the overestimation, the speaker doesn’t seem too worried, indicating a potential disagreement or controversy regarding the significance of the AI’s accuracy. 🔄 The use of AI-based tools like the code interpreter raises controversy around the potential replacement of human data analysts. 💡 The potential functions of the chatbot can range from filtering and aggregating data to generating visualizations and even running SQL queries, making it a versatile tool for data analysis. 💡 The AI model can recommend specific functions, such as the plot time series function with the metric sales, to visualize data and provide valuable insights to the user. 💡 Using function calling to develop custom agents that can act as data analysts is a promising approach with several advantages, including full control over generated plots. 🚧 Implementing guardrails and integration tests can help ensure the reliability and accuracy of AI-based business data analysts. PUBLICATION PERMISSIONS: PyData provided Coding Tech with the permission to republish PyData talks. CREDITS: PyData YouTube channel: @PyDataTV