Best Practices

Recommended setup

Use the "Changed after" filter for large workspaces

If your workspace has thousands of tasks, set the Changed after date to limit exports to recently modified records. This avoids timeouts and keeps your destination lean.

Export Tasks and Users as separate sources in one data flow

Add both Tasks and Users as sources, then use the Join transformation on assignee ID. This gives you a clean table with task details and assignee info combined — ideal for workload dashboards.

Use Append to combine multiple workspaces

If your team operates across multiple Asana workspaces or accounts, add each as a separate source and use the Append transformation to merge them into a single dataset.

Data refresh and scheduling

Run incrementally, not as a full refresh

For Tasks, use the Changed after filter combined with an Append destination mode. This adds only new or updated tasks each run rather than reloading everything — faster and less prone to timeouts.

Schedule Stories exports less frequently

Stories (comments and activity) grow quickly. A daily or weekly schedule is usually sufficient — hourly exports of Stories can be heavy on API calls and slow to process.

Performance optimization

Extract custom fields with json_extract

Custom fields come back as a JSON blob. Use Coupler.io's calculated column with json_extract to surface the specific fields you need — this makes downstream filtering and reporting much easier.

Send data to BigQuery for large-scale analysis

If you're tracking hundreds of projects or need historical trend data, BigQuery handles Asana's volume much better than a spreadsheet. Use incremental loads to keep costs low.

Common pitfalls

Do not connect a personal Asana project space. Asana's API blocks access to personal spaces entirely — you'll get a "Data cannot be fetched" error every time. Make sure you're using an organization workspace before setting up your data flow.

Do

• Verify your account is part of an organization workspace before connecting

• Use the Changed after filter to scope large Task exports

• Use json_extract for custom fields you need as separate columns

• Test with a manual run before setting up a schedule

Don't

• Expect to filter Tasks by project ID at the source level — do this post-import

• Try to export media attachments — only structured data is supported

• Export all Stories on a high-frequency schedule — it's slow and rarely necessary

• Assume empty columns are a bug — fields like completed_by.name are only populated in specific conditions