**Our Take: When shared edits stall your refresh, discover a simpler path forward.**
This user's problem is a clear signal that traditional spreadsheet architecture has reached its limit. A setup that worked reliably for a year suddenly breaks, not because the user did anything wrong, but because the tools they're using were never designed for the way they actually work. When edits on one machine cause PowerQuery to refresh for hours and then fail with a memory error, the culprit isn't the VM or the cache. It's the foundational assumption that a file-based, sync-dependent workflow can handle modern data complexity without friction. This isn't a user error; it's a product limitation.
Think about what this user has built. A single workbook pulls from online sources, Dropbox, SharePoint, OneDrive, and local tables. It runs merges, custom formulas, and variable parameters controlled by a dropdown. That's not a spreadsheet anymore, it's a data pipeline. And data pipelines need a runtime that understands dependencies, tracks versions, and resolves conflicts. Excel and PowerQuery treat the file as the source of truth, but the user's actual source of truth is the data itself, spread across multiple machines and platforms. When one computer edits a shared file and the other tries to refresh, the system has no way to reconcile what changed. It keeps retrying until it runs out of memory.
What this means for you is straightforward: if your workflow involves more than one machine, more than one data source, or more than one person, you're already pushing past what a local spreadsheet can handle gracefully. The moment you start syncing files via Dropbox and editing on separate machines, you've introduced a coordination problem that no amount of cache-clearing or reinstallation will solve. The user reinstalled their entire VM and the problem returned immediately after the next cross-machine edit. That's not a bug, it's a design constraint.
The practical takeaway is that the solution isn't to find the right cache folder or the perfect refresh sequence. It's to move your data logic into an environment where sharing and editing are native features, not afterthoughts. An AI-native spreadsheet, for example, treats every query as a live connection to a central model, not a file that has to be manually synced. Edits on any machine update the model, not a copy. Refreshes become instant because the system knows exactly what changed and doesn't have to reprocess everything from scratch. The user's elaborate PowerQuery setup is a testament to their skill, but the energy they're spending on workarounds could be spent on actual analysis. Stop fighting sync conflicts and start asking what your data is trying to tell you.