ChatGPT’s Code Interpreter: What’s The Fuss?

The AI Future Of Data Analysis

Have you ever wished you had a data analyst on staff to help you make sense of the numbers? With ChatGPT’s Code Interpreter, that wish just might come true.

Code Interpreter is an add-on feature within ChatGPT that allows you to run code and analyse data, even if you don’t have a data analyst on staff. You can upload spreadsheets, gather and visualize data, create charts, and perform sophisticated math with just a few simple prompts.

But Code Interpreter isn’t just for basic data analysis tasks. It’s surprisingly adept at more complex tasks as well. Wharton Professor Ethan Molick has even used it to upload unformatted data from a PDF and perform full data analysis, restructuring the data and formatting in the process. And Code Interpreter can run models and reason about the results from seemingly simple prompts.

To perfectly illustrate the utility of Code Interpreter, Paul Roetzer gave this example of how he used Code Interpreter on the AI Marketing podcast:

• Roetzer created an AI talent index using LinkedIn sales navigator data and built a workbook where he could find the most likely job titles and industries where AI adoption would be sooner than others. That was pre-ChatGPT and hard to find people who were adopting AI into organisations.
• Now, with ChatGPT’s Code Interpreter, he can upload all the raw LinkedIn data in a google spreadsheet straight into ChatGPT and instruct the AI to review the data set and identify the best titles and industries to target for AI education and events.
• ChatGPT first went through and did an analysis of the data set and identified that it was a list of different job titles with corresponding functions and metrics related to adoption and impact of AI and automation.
• However, ChatGPT went further with a column by column interpretation of what the data is to determine the best titles and industries we can consider roles with high AI adoption likelihood.
• At this point ChatGPT starts analysing the data it comes back with the top 10 job titles to target for AI education and events. It then like force ranks the top 10. It then goes through and ranks the top seven industries based on size.
• Roetzer explained how he went on to ask ChatGPT to create visualisations to help tell the story of the data and market opportunities? Code Interpreter created two bar charts that showed the data by title and by industry and analysed those and explained the information it was showing.
• ChatGPT then went through and gave him eight different things he should think about enriching this data set with. Because code interpreter is not connected to the internet, it couldn’t do this itself, but it pointed him to look at current AI usage, gross of a role or industry, tech and technological readiness, regulatory environment, and other interesting data sets.
• Roetzer asked ChatGPT what questions should we be asking about this data set that could lead to interesting strategic insights?

“This is to me where it starts getting really interesting. This is the data analyst side where I may be a business leader, I may be a marketer. And I look at a data that’s like, I don’t know what to ask this thing.”

The point Roetzer makes is that everything he did, he did it in real time and without the expertise of a data analyst at his side. To take any data set, anything about churn, about growth, about audience, about persona building, about target markets, whatever it is, and just upload it into ChatGPT in any format or style document and ChatGPT will just analyse it.

The potential uses of this are massive.

Here’s The Thing: Code Interpreter isn’t going to replace human data analysts. It’s a tool to complement their work. And while it can operate at the level of a pretty good grad student on most data analysis tasks, it still makes occasional mistakes and bad choices that a more experienced human would not.

But for companies that don’t have data analysts on staff, Code Interpreter can provide the data analysis capabilities they need. And even for those that do, it can help them work more efficiently and effectively.

So the question becomes: is Code Interpreter the future of data analysis? Will it eventually replace human data analysts altogether? It’s hard to say for sure, but for now, it’s a powerful tool that can help companies make sense of their data and make more informed decisions.

And who knows, maybe someday we’ll all have a virtual data analyst on staff, thanks to tools like Code Interpreter.

You can listen to this snippet from the AI Marketing podcast here on SNIPD.

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About The Author

Rick Huckstep is a write, podcaster and YouTuber with a passion for emerging technologies and the way they will shape tomorrow’s digital world.

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This article was written and created with the use of AI tools including NotionAI and Canva.

Originally published at https://rickhuckstep.com on July 13, 2023.