Enhance your data and financial analysis capabilities by leveraging AI tools such as ChatGPT and Copilot. Learn effective strategies for finding, analyzing, and visualizing datasets to uncover valuable insights and trends.
Key Insights
- Source relevant datasets from internal company resources, Kaggle.com, or financial statements like 10-K and 10-Q reports for use with AI analysis tools.
- Conduct preliminary assessment to identify dataset formats, cleanliness, and structure, and leverage AI tools like ChatGPT or Copilot to assist in data cleaning and preparation.
- Combine targeted and open-ended analytical approaches—calculating specific metrics (e.g., sales figures) and allowing AI to suggest potentially unnoticed insights, trends, and visualizations to enrich your analytical portfolio.
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If you need to do data analysis or some sort of financial analysis, see how AI can help you in this process. The first challenge is to find some data sets you want to analyze. Of course, if you're working within a company and there's some data, that's ideal, so you can actually be running this on stuff that you're already familiar with, that you get from your company.
If you don't have a particular data set available that you want to use, you could also head over to Kaggle.com, which has some crowdsourced data sets that you can download, find something that you're interested in that you want to do some analysis on. A lot of these are CSV files that you can use in ChatGPT or in Copilot. The other thing you could also do is find financial statements, such as a 10k or 10q, and you can get them from some various websites.
Download those, and once you have decided your data set that you're going to work with, first thing is you need to understand at least what's going on, like what kind of data do you have, what content is in there, and what is the structure, like what kind of columns do you have if it's a CSV or Excel file or Google Sheet or something like that. So what kind of data do you have, what formats it in, does it need to be cleaned up before you do anything, does ChatGPT or does Copilot have to help you doing that cleanup, are you going to do that cleanup? And think about at least three different analytical questions that you want to explore. If you have specific types of things that you regularly do in your job, think about those regular types of things that you do and do it on your data set.
If you don't typically do this and you just want to explore doing data analysis, think about things that you'd be interested in knowing about the company or data set that you're working with and ask it various questions. Or you can also say with this data set, what are some things that ask ChatGPT or Copilot to say, what are things that you think are worth analyzing? Do you see anything that's interesting in this data that you'd want to point out to me? You don't always have to go in knowing exactly what you want to look for, but I would say take both approaches. Go in looking for something specific, like talk about things like how much sales calculate something.
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So try to do some calculations and also ask it those open-ended questions about do you see anything that's interesting in this data that I might not notice? Do you see any trends? Those can be some interesting insights that maybe you didn't even think about, but AI can find those interesting data points. And then you can ask ChatGPT or Copilot to generate charts or graphs or do summaries based on your questions. And then you can take all of those and put them together and highlight the key findings and insights, and that can be part of your AI portfolio.