When spreadsheets reach their limits: using BigQuery with Sheetgo

Google Sheets is where most teams start. It's flexible, familiar, and works well until the data outpaces the tool's capacity
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The signs show up gradually: the file takes 30 seconds to open. Formulas return errors instead of results. Someone adds a new data source, and half the sheet stops calculating. The team starts splitting files to manage the load, which creates a new problem. Now the data lives in five places, and nobody has a complete view of anything.
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Google Sheets has a hard limit of 10 million cells per file. For teams with multiple data sources and growing datasets, it's not a question of if you'll hit it — it's when.
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BigQuery removes that ceiling.
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With Sheetgo, you can move your data from or into BigQuery automatically, without rebuilding your workflows from scratch. Once your data is there, you can run queries across millions of rows in seconds and keep your Sheets connected for the parts of the work that still make sense there.

A useful signal: if your team is spending more time maintaining the spreadsheet than actually using the data inside it, it might be time to make the move.
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