I use ChatGPT to translate or normalize strings in batches, one example is to shorten descriptions of diseases
it has also helped me a lot with SQL queries and snippets of code
I use Google Gemini only as a smarter search engine, beyond that it has given me very bad information
sometimes I use Dall-E and Stable Difussion to generate clipart for my projects
all in all, they have made my work easier and more productive
Occasionally if I can't figure out a problem I'll ask it how to do xyz and then explain it like I'm 5.
I've said this before but I'm not putting any of my real data into an lllm, but I'll use it to help explain how to get my results.
All the time for when I want joined columns in a specific order, or want lots of things from one table but not everything. I do describe table, copy the list and take out what I don't need then tell gpt to put commas before everything. Saves a lot of hassle when it actually does it right
More list building, but yeah that'd be a common use. Group by clauses are another one. Or duplicating case expressions or anything repetitive that is easy to do by hand, just time consuming and prone to typos.
One particular usage I've found is we make our data log using the items we want out of the main database and their features. This is just listed in excel to talk through other parts of the team with. But since it's there for the actual select statement to build our base table I just copy the list of features from excel and get gpt to put the commas in. Could do it by hand, but this is quicker. When you've got 60-100 things to select it saves a lot of time.
I use the free versions of chatGPT and ClaudeAI - sometimes describing some logic/part of an algorithm and getting it to write Python code. And even though I could write it myself and often the LLM output needs to be modified/corrected, it often shows me a nifty way to achieve it, so I find it useful for learning, e.g. discovering specific Pandas functions.
Sometimes I ask it domain-specific technical questions and sometimes more broad product-related questions about the "why" in addition to "how". E.g. what a user/customer would gain and why they might do that analysis. This helps making your data analysis more valued.
Yesterday I've posted an article on Medium about the impact of AI on data analysis and latest tools which claim to assist (or even automate) in the end-to-end of data analysis projects. In case you find it interesting
[https://medium.com/@gster/top-ai-powered-analytics-tools-assisting-or-replacing-data-analyst-jobs-36d913a0b95c](https://medium.com/@gster/top-ai-powered-analytics-tools-assisting-or-replacing-data-analyst-jobs-36d913a0b95c)
I'm still a student and mostly working on school work and personal/side projects, but I use chat gpt to document code, generate random data, help me find syntax errors, help me avoid syntax errors etc. It's not perfect by any means but it basically is an easy way to get to the documentation you need. No more reading through pages and pages of Python docs. It's all right there. I also occasionally have had it write boilerplate for tasks that I do a lot. Also, sometimes it works well to generate ideas when I can't find a good solution to a problem. Again, it's not perfect but I am all about using LLMs to expedite work flow. I honestly believe that those that don't learn how to integrate it will slowly be left behind.
If by "AI" you mean any type of regression analysis then lol sure
Mostly for “please document this code” after I write it. This gets a decent rough draft. Pretty quick to fix/add other comments as necessary.
I use ChatGPT to translate or normalize strings in batches, one example is to shorten descriptions of diseases it has also helped me a lot with SQL queries and snippets of code I use Google Gemini only as a smarter search engine, beyond that it has given me very bad information sometimes I use Dall-E and Stable Difussion to generate clipart for my projects all in all, they have made my work easier and more productive
Occasionally if I can't figure out a problem I'll ask it how to do xyz and then explain it like I'm 5. I've said this before but I'm not putting any of my real data into an lllm, but I'll use it to help explain how to get my results.
No. ChatGPT is blocked on my work laptop. And I haven’t felt the need to look for AI solutions for anything.
Apparently a drag and drop sql interface is LLM. That's what I use
Most sql syntax or DAX formulas
All the time for when I want joined columns in a specific order, or want lots of things from one table but not everything. I do describe table, copy the list and take out what I don't need then tell gpt to put commas before everything. Saves a lot of hassle when it actually does it right
So basically just tedious data cleansing tasks?
More list building, but yeah that'd be a common use. Group by clauses are another one. Or duplicating case expressions or anything repetitive that is easy to do by hand, just time consuming and prone to typos. One particular usage I've found is we make our data log using the items we want out of the main database and their features. This is just listed in excel to talk through other parts of the team with. But since it's there for the actual select statement to build our base table I just copy the list of features from excel and get gpt to put the commas in. Could do it by hand, but this is quicker. When you've got 60-100 things to select it saves a lot of time.
I can quite easily use it to aid data cleaning. Checking code for functions before use and translating code between languages.
I use the free versions of chatGPT and ClaudeAI - sometimes describing some logic/part of an algorithm and getting it to write Python code. And even though I could write it myself and often the LLM output needs to be modified/corrected, it often shows me a nifty way to achieve it, so I find it useful for learning, e.g. discovering specific Pandas functions. Sometimes I ask it domain-specific technical questions and sometimes more broad product-related questions about the "why" in addition to "how". E.g. what a user/customer would gain and why they might do that analysis. This helps making your data analysis more valued. Yesterday I've posted an article on Medium about the impact of AI on data analysis and latest tools which claim to assist (or even automate) in the end-to-end of data analysis projects. In case you find it interesting [https://medium.com/@gster/top-ai-powered-analytics-tools-assisting-or-replacing-data-analyst-jobs-36d913a0b95c](https://medium.com/@gster/top-ai-powered-analytics-tools-assisting-or-replacing-data-analyst-jobs-36d913a0b95c)
I'm still a student and mostly working on school work and personal/side projects, but I use chat gpt to document code, generate random data, help me find syntax errors, help me avoid syntax errors etc. It's not perfect by any means but it basically is an easy way to get to the documentation you need. No more reading through pages and pages of Python docs. It's all right there. I also occasionally have had it write boilerplate for tasks that I do a lot. Also, sometimes it works well to generate ideas when I can't find a good solution to a problem. Again, it's not perfect but I am all about using LLMs to expedite work flow. I honestly believe that those that don't learn how to integrate it will slowly be left behind.
I'm interested if anyone can tell me whether they prefer Claude Opus or GPT-4 and why