Introduction
Chat GPT has been in the news quite a bit recently. It’s been just about a year since it was released and everyone is using it to help them be more efficient and do better work. The creativity use case for it is quite obvious since it can help inspire and spark ideas but what about use cases that are more technical such as data science and data analytics? That’s what the article “How To Use ChatGPT: Data Analyst & Data Scientist Use Cases” by John Pauler details(the article can be found here).
Summary of Article
The article first starts out by mentioning why people need to learn how to use Chat GPT: it can make you more effective. It then gets into the job scenario for data analysts and shows that even though AI is good at the technical aspect of analysis it still lacks some other soft skills that analysts need to thrive so the job case for analysts for the “foreseeable future” is still there. The article then gets into some words of wisdom for using AI and it boils down to using common sense. Don’t share private information, AI isn’t always right, do your due diligence, AI isn’t capable of human common sense so make sure you use your basic judgment before doing anything. After, the article gets into some best practices for using AI tools for analytics and shows you how to tweak your prompts into chat gpt to ensure that the AI provides you with the example you are looking for, things such as providing context and being specific go a long way. Then the article lists different things that “Data Pros” can use Chat GPT for. These include generating code, troubleshooting, adding comments to your code, performance optimization code, automating manual tasks, providing tips, explaining concepts, and more. Finally, the article lists some of the use cases for the use of chat gpt in different applications such as Excel, Google Sheets, Power BI, SQL, and Python.
My Take
Overall, this article was a good one. It gives a lot of actionable things that one can implement as soon as they are done reading which is appreciated. It is structured in a very easy-to-read format which helps to read and understand. One thing that I would have liked however is for the article not to touch on so many points so briefly and kept to fewer points but explained them more in detail. This would have helped to deepen the understanding of what Chat gpt can be used for in this field and that coupled with the actionable examples that the article already gave would have been great. One more thing I liked was the color scheme, it does wonders to capture you and to keep you captivated and it looks nice. This really made the reading more enjoyable.
Conclusion
All in all, this article was a good one. It was one which, although a little too much breath and not enough depth in my opinion, was very informative and gave a lot of actionable things to take away from this article making it very helpful. I highly recommend you read it when you get the chance(the link can be found here).