We have a straightforward opinion on this: the problem isn't your dataset, it's the tool you're using to manage it. For years, the spreadsheet community has treated performance slowdowns as a user error, a sign that you need to optimize formulas, reduce volatile functions, or restructure data. That mindset is a relic of a pre-AI era, and it's costing you time and insight.
The user who posted this question, beachlady38, is clearly skilled. They've already experimented with best practices: minimizing whole column references, cutting back on volatile functions. They're looking for Power Query tips and data organization strategies. These are smart moves within Excel's limits, but they're workarounds, not solutions. Every hour you spend troubleshooting lag is an hour you could spend actually analyzing your data. The real question isn't "How do I make Excel faster?" It's "Why am I still using a tool that treats a large dataset as a problem rather than an opportunity?"
Consider what beachlady38 is describing: slower load times, lag with filters, formulas that choke. These aren't signs of poor spreadsheet hygiene. They're symptoms of a tool designed for static tables, not dynamic, growing data. The community's advice will likely be helpful, turn off automatic calculations, use Excel Tables, split data across sheets, but each fix is a patch. None of them address the core issue: spreadsheets were not built for the scale and complexity of modern data work. You shouldn't have to architect your entire workflow around avoiding slowdowns.
What this means for you is simple: if you're spending more time managing performance than managing your analysis, it's time to explore tools that match your ambition. AI-native spreadsheets don't just handle large datasets, they thrive on them. They process calculations in memory, not row by row. They let you ask questions in plain language and get answers without rebuilding formulas. The goal isn't to make Excel faster; it's to make speed irrelevant. Start by asking yourself what you'd do with your data if lag wasn't a factor. Then find a tool that makes that possible.