Can chat you with you really replace data analyst as I did it and always? Should you be bored about your job and what’s going to happen in the end as these AI tools keep getting smarter every day? Well, that’s a question that makes everyone worried and concerned. But fear not, I’m here to give you a solution.
Hey guys, what’s up? This is Ali, I’m back with another video. In this video, we’re gonna take a deeper look into this particular tool to see what our GPD30 or 4 is fully capable of taking over all data analysis roads or not.
If your work involves analyzing and reporting on data, it’s totally understandable that you might feel a bit concerned by the rapid advances being made by artificial intelligence. So, what would you do to take advantage of AI instead of getting depressed or even unemployed at the end of March 2023? Open as charging with the realistic plugin called code interpreter. Right, but I think they recently changed to the advanced in analysts. But overall, this tool can do pretty advanced problem-solving job.
After this, a lot of people are claiming that this is gonna take away data analysis jobs. You can upload a data file into it and involve Python to perform regression analysis and descriptive analysis. Look for patterns in your data and even create visualizations, all without having to write or even know a line of Python code.
So, if you have access to the Chat GBD4, follow my steps. First, open up ChatGPT and prompt, ‘What type of file can I import?’ Then, you’re going to see this plugin can understand all these formats. Okay, let’s get started with CST Pi. All you have to do is just drag your file and drop it into the chat field. Then, write this prompt: ‘You are a data analyst with this CSP and perform some exploratory analysis.’ Then, you’re gonna see it’s gonna start analyzing your data and it’s going to tell you what your CSV is about. More interestingly, all of this is done by Python code that is available for you to see. That’s insane, isn’t it? And also, this tool is fully able to tell you what your dataset is about and can even perform exploratory data analysis and finally produce some visualizations. That’s pretty good, but that doesn’t end here.
I do a simple look that all LLMS or large language models need to be trained by prompts or different types of data in order to get the best possible accuracy, which might take time or might be happening all the time. Versus, this tool has some limitations like the number of entries or requiring active internet connection that might be needed for loading files from Google Sheets and more importantly, this is a skill that GPD4 just automated. Where harder skills but chargeability cannot replicate the full range of soft skills that the human data analyst can.
Now, let’s look at essential surface kits that this tool cannot process. Number one is critical thinking. While companies need someone who can think critically about their data and their insights, AI cannot critically analyze or solve complex problems. Number two is communication. AI lacks the human touch in communicating data insights. Number three is domain knowledge. AI doesn’t have that curiosity for domain nuances. Number four is ethical judgment. Making ethical decisions is beyond AI’s capability. Number five is flexibility. AI cannot adapt to new or unforeseen situations, whereas human data analysts can be someone flexible all the time. And number six is contextual understanding. AI struggles with understanding broader context, at least for now. It might be fixed in the near future.
It is possible that ChatGPT and other large language models could replace certain jobs that involve primarily data analysis, report writing, or other tasks that can be automated. However, it’s important to note that a large language model like ChatGPT is not capable of understanding context or meaning in the same way that humans do and are not able to replace many jobs that require critical thinking, creativity, or human interaction. Additionally, the use of a large language model like ChatGPT is likely to lead to changes in the job market rather than the complete replacement of jobs. Consequently, to avoid redundancy, data analysts should embrace AI as a tool and leverage its capabilities for routine tasks, and focus on areas that require human expertise and adapting to the evolving landscape.
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