I didn't know you could make a request like that. However for my own personal privacy and my particular use case in my more professional I can't use it for certain things. It is also highly limited in the ChatGPT interface: If I give it a small psuedo data set with plausbible date (6 columns, 8 rows) and ask it to do something basic like format it into a table it will start to do that but cut off when it gets to row 6, column 5.

I then remind it that it didn't complete the table, it apologizes, reattemps, and still truncates things. It's output is still far shorter than what I receive in some other prompts so it's not purely a length issue. I'd need to have control to tweak its parameters through the API to get it to respond appropriately.

However, while it may not format the table well, it will still keep the full data set in memory and answer questions on it. For example, I told it the data context. I then asked it why one category (row) saw a decline for a specific year (the columns) and it gave a cogent insightful answers that only my boss and I, the domain experts in my organization, would be able to identify so quickly.

I then asked it to make a projection to a following year, where the data was not given, based on the observed data. I did so. The values were reasonable, but I didn't know why it used them, so I asked it where it got them from, why it chose them:

The answers where incredibly cogent, again on the level that an entry level junior domain expert would give. Here's one nearly verbatim for one of them from my memory. It said "I noticed that the values were consistent for most years but dropped significantly for one year, but the most recent year recovered to an even higher level. So I projected a value that was less than the most recent year but still mostly approximated the average outside of the anomalous year. It gave a bullet point explanation like this for each of the eight rows.

I asked in WHY the drop may have occured that year, and again I had told it the data context so it knew what the data was about, and it have 5 bullet pointed paragraphs that, again, would be very solid answers for a junior practitioner in my area of work.

I asked it was specific formula calculations it used for the projections it mentions. It then apologized for not clarifying earlier (lol, it does that a lot) and then proceeded to tell me that its initial projections were qualitative in nature base on observational criteria. That alone is amazing. In then went further though, without more prompting to say something very much like "However if you would like a more quantitative approach the following formula would be a reasonable approach"

It then went on to describe in great detail the formula I could use to calculate the difference from year to year for each row of data and apply that average to the next projected year's #, along with explaining its reasoning in detail for each step it took.

ChatGPT 3.5 gave very basic answers that I suppose might be useful for a basic user looking for basic possibly trends, as long as they understood that it could be total BS and they needed to vet the answers. GPT-4's analysis was spot on

I can't fully express the extreme utility of this. Giving GPT-4 a pre-aggregated data set to have it give some decent insights automatically could save me hours of work reviewing & finding some of the most obvious trends that would be obvious to me when I see them but would require me to look through 10 to 50 columns of data across 20 to 100 rows of data (keep in mind it would be predigested, cleaned and validated data so work has to be done to get to that point.)

But then GPT-4's preliminary observations would bootstrap my ability to digest the rest of it and have a jumping off point to perform more complex analysis. Then I could give it bullet points and have it summarize my findings in a digestible way for my less data-literate audience, all told saving me hours and getting me out from under a huge backlog of work.

It's a use case that would in no way threaten my job, but make me more productive. And I have enough work that I'm hiring a junior data analyst, and would need to do so even with this increased productivity, and so it would not deprive them of a job either.

It truly would (will!) be a game changer in my day to day work. But I do fully acknowledge that it would, in some other areas of work, reduce the # of employees required to fill the available work. And also that to my fear, future versions could make me less relevant as well, though I think that's further off. Domain expertise is an enormous part of my job.