Asana Data Not Updating for ~4 Hours After Refresh (API / Gateway)

[snehaj214]

HiTrying to link Asana to PowerBI  Setting Up Asana API for Power BI – Detailed Instructions Needed 

I am connecting Asana to Power BI using the Asana connector. I tested both manual refresh in Desktop and scheduled refresh via gateway in the Service.

The refresh completes successfully with no errors, but updates made in Asana do not appear in Power BI for about 4 hours. After roughly 4 hours, the changes suddenly show up.

I found documentation stating that exported data with more than 1,000 tasks refreshes every 4 hours, and that reloading within that window completes successfully but does not return the latest data. My dataset contains more than 1,000 tasks.

Has anyone experienced this 4-hour delay?

Is this a limitation of the Asana connector, Power BI caching, gateway behaviour, or an Asana API restriction?

Any insights would be appreciated.

[v-kpoloju-msft]

Hi @snehaj214l, 

Thank you for reaching out to the Microsoft Fabric Community Forum. Also, thanks to @Ritaf1983,  for those inputs on this thread.

Has your issue been resolved? If the response provided by the community member @Ritaf1983,  addressed your query, could you please confirm? It helps us ensure that the solutions provided are effective and beneficial for everyone.

Hope this helps clarify things and let me know what you find after giving these steps a try happy to help you investigate this further.

Thank you for using the Microsoft Community Forum.

[Ritaf1983 · Accepted solution]

Hi @snehaj214 

The 4-hour delay is a documented Asana API limitation, not a Power BI or Gateway fault. For datasets exceeding 1,000 tasks, Asana generates a cached export file that only refreshes every 4 hours. Any refresh triggered within this window pulls the same cached data.

To resolve this, you must bypass the native connector:

Direct REST API: Use the Web connector in Power BI to call the Asana API directly. This requires M code for authentication and pagination but retrieves real-time data.

Middleware: Sync data to a SQL database using ETL tools (like Power Automate or Skyvia) and point Power BI there.

Data Partitioning: Reducing the scope to under 1,000 tasks per request avoids the export cache logic.

The native connector prioritizes stability for large datasets; high-frequency refreshes require a custom API approach.

If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly