> The problem is I dont have the time to code every single visualization from scratch Unfortunately, most chat-based AI tools fail once they hit the 100k row mark due to context window limits. I had issues with accuracy on similar retail sets last month, tbh. You should check out Microsoft Power BI Pro. It uses AI to auto-generate DAX and visuals directly from your SQL tables. Quick tip: keep your data types consistent in SQL before importing to save hours of troubleshooting.

You might want to consider PandasAI Pro Cloud Platform for those messy files. It is way more reliable for large sets because it generates the code to run locally instead of trying to read all the data into a chat window. Be careful tho, if your headers are inconsistent it might trip up. Make sure to clean the spreadsheets first or itll definitely struggle with those Chicago retail trends... dont trust the auto-cleanup blindly.

> I really need to get some solid insights by the end of next month for their Q4 planning session. If accuracy is the main worry, you gotta be careful with bots that just hallucinate trends. I have been messing around with Gigasheet Premium Big Data Spreadsheet lately and it handles huge files way better than a standard chatbot. It basically lets you upload those massive CSVs or connect to SQL without the rows timing out. It has a built-in AI assistant that uses a logic-first approach, so its less likely to just invent numbers because its looking at the actual data structure instead of just guessing from the text. Another decent option is Rows.ai Business Plan. It feels like a regular spreadsheet but integrates with LLMs to clean data. The safety aspect is better because you can see the formula it generates. If you are dealing with hundreds of thousands of rows, Gigasheet is probably more stable tho.

• Upload the messy spreadsheets to their cloud
• Use the data cleanup tools first to fix headers
• Then run the AI insights for the Q4 trends It fits the $60 budget too. Just make sure you double-check the aggregations against a manual pivot table for a small sample just to be 100 percent sure about the reliability before the meeting. Ngl, retail data is always messier than it looks... basically a nightmare if you dont clean it first.

Just saw this thread and had to jump in because I have been through the ringer with these tools over the years. Honestly, most of those chat with your file apps are just toys once you hit 100k rows. For a project like yours—especially with those messy Chicago retail sets—you need something that doesnt choke on the SQL connection. I ran into the same wall a while back and switched to Coefficient AI for Google Sheets. It connects straight to your SQL DBs and lets you use AI to clean up those rows right inside the spreadsheet. Since its pulling data directly, you dont get those annoying timeout issues you see in ChatGPT. Another solid one I have used is Rows Plus Spreadsheet AI. It is basically a modern spreadsheet that has a built-in AI analyst that handles the crunching without hallucinating numbers like a standard bot might.

• Handles massive imports from SQL without crashing
• AI-powered data cleaning for those messy spreadsheets
• Fits well within your 60 dollar budget In my experience, you are better off using a tool that lives where your data actually sits instead of trying to upload massive CSVs to a bot that doesnt understand relational tables anyway... just save yourself the headache.

Honestly, for that volume of retail data, the standard ChatGPT interface is gonna let you down. Ive hit those same timeout limits when trying to process multi-year sales trends. If you want to stay within that $60 budget, you should look into Julius AI Pro Plan. Its specifically built for data science and handles massive spreadsheets much better than a general-purpose chatbot. It writes the Python code in the background to process your data, so youre not just relying on the LLMs memory to do math, which is where the hallucinations usually happen. Another solid path is Anthropic Claude 3.5 Sonnet. I find its coding logic for data cleaning way more robust than GPT-4o. If your data is in SQL, you can use Claude to write the complex joins and cleaning scripts, then run them locally. If you are dead set on an all-in-one tool, Akkio Business Plan is right at your price point and handles lead scoring and trend forecasting without needing to code. Its way more reliable for retail sets than just tossing a CSV into a chat window. The key with these large sets is to make sure the AI is generating code to analyze the file rather than trying to read the whole thing into its context. Thats why those timeouts happen. Julius tends to be the sweet spot for people who need the power of Python without the time sink of writing every matplotlib line manually... it basically manages the compute environment for you so the file size dont crash the browser session.