Here are the Top AI Tools for Research Data Analysis

In this video, I dive deep into the world of AI tools and how they can transform data analysis. AI has become an essential part of data science, helping us extract meaningful insights from complex datasets. I decided to test three popular AI tools to find out which one excels in data analysis: Julius AI, Vizly, and the latest version of ChatGPT.

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I started with a public healthcare dataset, which is perfect for evaluating the capabilities of these AI tools. First, I input the data into Julius AI and was impressed by the range of visualizations it produced, such as the distribution of hospital codes and stay lengths. One feature I particularly liked about Julius AI is its self-correcting mechanism, which ensures the analysis remains accurate.

Next, I tested Vizly. This tool also provided insightful visualizations and added a layer of interactivity with its graphs. I could zoom in and out and interact with the data points, which made the analysis more engaging. However, it had some limitations when dealing with more complex, unstructured data.

Finally, I turned to ChatGPT for data analysis. This tool stood out with its ability to create interactive graphs and its thorough analysis plans. One feature that set it apart was its ability to hold metadata in memory and provide a step-by-step breakdown of its analysis process. ChatGPT was also able to confirm its findings by recalculating efficiency, which added an extra layer of reliability to its results.

AI helps in research by making data analysis more efficient and accurate. Whether you're dealing with structured or unstructured data, these AI tools can provide valuable insights that can drive better decision-making.

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▼ ▽ TIMESTAMPS
00:00 Intro
00:09 Looking at the data
00:35 The first prompt
04:54 Text file data
11:18 Can they be broken?

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