Unlocking Dataset Potential with ChatGPT: A Beginner's Guide to AI Data Analysis

In today's data-driven world, having access to vast amounts of information is just the starting point. The real challenge lies in extracting meaningful insights and trends from this data. That's where AI tools like ChatGPT come in – making complex tasks like data analysis more intuitive and accessible than ever.  The purpose of this blog and video is to show you how a simple chat can unlock the potential of any dataset, and provide a flexible method for approaching data analysis that can be utilized by both novices and experienced analysts. Ultimately, I hope to demystify this experience and help you start trying it out for yourself!

Before we dive into the nitty-gritty of data analysis, let's cover the basics. To provide data to ChatGPT, you can upload various file types, including CSV, Excel, and JSON files. For those that don’t already have data they’d like to analyze, Kaggle.com offers free datasets that often have specific types of analysis for you to practice.

With that out of the way, lets look at our first prompt

Help me prepare this data for analysis. Evaluate the data set for data entry errors and create a cleaned version of the data if you do find errors. 

When doing any type of analysis its important to be certain that you data doesn’t contain any errors that may affect the results.  This is a very simple prompt in its structure: we start with our primary task which is “help me prepare this data for analysis” and the rest of the prompt is just an explanation for how the chatbot can be most helpful. This is the type of task that ChatGPT is very good at, but it's always a good idea to double check its work to make sure it didn’t misunderstand you or make any mistakes. 

Once we’re done preparing our data we’re ready to move on to actual analysis, starting with the most basic possible approach.

Analyze the data for trends

Despite not being even a full complete sentence, this is everything ChatGPT needs to get started. You may even get meaningful info from just saying “analyze” but it will most likely ask what type of analysis you want so specifying, at least generally, what we’d like it to analyze for will save us that time. 

From here all you have to do is have an organic conversation with ChatGPT about the data to extract any further information or insights that you’d like.  You ask about specific relationships between data points, for insights based on trends, or even detailed explanations on aspects of the analysis that you find interesting (or confusing). 

This is what makes ChatGPT such an invaluable tool for beginners learning data analysis: you can come in with very little knowledge and ChatGPT can guide you through while also explaining its process and leaving you with a greater understanding than when you started.  As you get more experience, you can unlock even more power by narrowing ChatGPT’s focus to specific types of analysis you need and requesting specific visualizations that would be useful to you.

For those who are interested in this topic but don’t feel good about uploading their data to ChatGPT, definitely check out our recent video on hosting your own AI with Open WebUI that has a lot of the same capabilities! Both Open WebUI and ChatGPT offer options for creating custom models with specific instructions and a knowledge base that you can upload, allowing you to craft an assistant just for your data analysis needs!

That’s everything you need to get started doing data analysis with ChatGPT. These AI models allow us to approach increasingly complicated tasks with increasingly simple and intuitive ways, and data analysis is one of the use cases where this is shown most clearly.  

We hope you found this tutorial useful! If you have any questions please reach out to us.