Hi everyone! I'm new here and really hoping you can help me out. I've been trying to use Kimi to analyze sales data from a huge CSV export from our old CRM. The file is about 2GB with millions of rows, and whenever I try to upload it or even paste a sample, Kimi seems to give up and times out. 😅
I know the data has some yearly trends I need to spot, but I'm stuck on step one: actually getting the data into a shape Kimi can handle. I'm not a data scientist, just a sales ops person trying to make a case for new software!
What's the best way to format or break down a file this big? Should I split it by year first? Or maybe I need to remove most of the columns? I tried just taking the first 10,000 rows, but I'm worried that's not enough for Kimi to see a real trend.
Any basic tips on preparing massive files for Kimi would be so appreciated. I'm grateful for any guidance you all have.
Welcome! I've been in this exact spot with massive CRM exports. Kimi's great, but yeah, 2GB is just too much for it to chew through in one go.
Your instinct to split it is right. I'd start by cutting columns. You probably only need date, amount, maybe product line and region for a trend analysis. Strip everything else first. Then, splitting by year *after* that column purge is a solid next step. It keeps each file manageable and focused on the time periods you care about.
A random 10k-row sample might miss seasonal patterns. If you take, say, every 10th row to get a smaller but spread-out sample, that can work for an initial look. But for year-over-year, you're better with those clean, annual slices. Good luck
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Your first 10,000 rows are almost certainly the most recent data, which skews the sample. Don't do that.
user615 is right about cutting columns. You can do it in Excel by opening the CSV, deleting the columns you don't need, and saving as a new CSV. But 2GB might crash Excel.
If you're on a Mac or Linux machine, you can use the terminal. The command `cut -d, -f1,5,12` (adjust the numbers for your needed columns) on the original file is far faster. Google "cut command csv" for a quick tutorial.
Once you have just the key columns, then split by year. One file per year is a logical chunk for Kimi to analyze a trend. Trying to shove 5 years of raw data into it at once is asking for a timeout.
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Excellent point about the terminal being faster for column stripping. A lot of folks in sales ops might be on Windows though, and I've found that a free tool like CSVFileView or even Google Sheets (importing in chunks) can be a decent GUI alternative if the command line feels intimidating.
Just a heads-up on the column selection: before you run that `cut` command, open the original file in a text editor and note the exact column order. Sometimes CSV exports have weird headers or an extra metadata row that throws off the count. Getting that wrong means you filter out the data you actually need.