> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/files-and-tables/airtable-addon/best-practices.md). # Airtable Best Practices Airtable sync best practices — create view-specific flows, use dedicated import sheets, and manage refresh schedules for reliable data. ## Recommended setup


Create view-specific data flows	Don't share your entire Airtable base. Instead, create individual shareable views for each data flow. This gives you granular control over what data is exposed and makes it easier to manage multiple data flows.
Use a dedicated import sheet	Keep your imported Airtable data in a separate Google Sheet and reference it from your analysis sheets using formulas. This prevents accidental data loss when the import refreshes and overwrites your sheet.
Test with a smaller view first	Before setting up large imports, test with a small filtered view to ensure the connection works and data flows as expected. Once you're confident, you can scale to larger datasets.
Store passwords securely	If your Airtable view is password-protected, Coupler.io encrypts the password. Keep it safe, and update it immediately if compromised.

## Data refresh and scheduling


Choose refreshes wisely	Schedule automatic refreshes during off-peak hours to avoid rate limits. Daily or weekly refreshes are usually sufficient unless your data changes minute-by-minute. Manual refreshes are always free and on-demand.
Run manual tests first	Before setting up automatic refreshes, run at least one manual test import to confirm the link works and data looks correct. This prevents bad data from being scheduled repeatedly.
Monitor large imports	If you have very large Airtable views, run a manual import first to gauge how long it takes. Then schedule automated refreshes at intervals that won't cause overlapping imports.

## Performance optimization


Filter in Airtable, not in destination	Create separate Airtable views with filters applied instead of importing everything and filtering on the destination side. Smaller imports are faster and more reliable.
Hide unnecessary columns in Airtable	Only include columns you actually need in your Airtable view. Hidden columns won't be imported, making the import smaller and faster.
Split very large bases	If you have a massive Airtable base, create multiple data flows for different tables or views instead of importing everything at once. This reduces timeout risk and improves performance.

## Common pitfalls {% hint style="danger" %} **Don't put manual edits in your import sheet.** Coupler.io completely overwrites your sheet on every refresh. Any custom columns, formulas, or formatting you add will be lost. Create a separate analysis sheet and use formulas to reference the import sheet instead. {% endhint %} {% columns %} {% column %} **Do** * Share individual views, not your entire base * Use separate sheets for imports and analysis * Test imports with manual runs before automating * Schedule refreshes during off-peak hours * Create filtered Airtable views to reduce data volume * Store passwords securely if using protected views {% endcolumn %} {% column %} **Don't** * Share your full Airtable base link * Add custom columns to your import sheet * Run multiple large data flows simultaneously * Change your destination's timezone mid-project * Import fields with #ERROR! values from Airtable * Leave old data flows running if they're no longer needed {% endcolumn %} {% endcolumns %} {% hint style="warning" %} **Beware of special characters in multi-select fields.** If your data contains the delimiter character you chose (like a comma in a name), values may split unexpectedly. Pick a delimiter that doesn't appear in your actual Airtable data, such as a pipe `|` or semicolon `;`. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.coupler.io/sources/category/files-and-tables/airtable-addon/best-practices.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.