Hi Team, what is the best way to figure out why visualizations are loading slowly.

To understand why visualizations are loading slowly, the most effective approach is: 1. Check the exact SQL GoodData runs (

/debug

) - Open the slow visualization in Analytical Designer. - In the URL, replace

/edit

with

/debug

(e.g.

.../edit

→

.../debug

). - This downloads a debug file containing the SQL GoodData sends to your database. [[Query debug](https://gooddataconnect.slack.com/archives/C01UR5BGAHY/p1742904562356189?thread_ts=1742904562.356189&cid=C01UR5BGAHY); [Snowflake case](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1742221070310609?thread_ts=1742221070.310609&cid=C04S1MSLEAW)] - Run that SQL directly on your DB to see if the slowness is already there (long execution, heavy joins, timeouts). 2. Use DB performance tools / logs - In your database (Snowflake, Postgres, Redshift, etc.), look up the GoodData-generated query from the debug file and check: execution time, queue time, and which tables/columns are most expensive. [[Performance guidance](https://www.gooddata.com/docs/cloud/connect-data/performance/); [Explore timeout](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1721144102677359?thread_ts=1721144102.677359&cid=C04S1MSLEAW)] 3. Isolate which part of the visualization is heavy - On the same insight, remove metrics one by one or change their order: - The first metric acts as the “driver” for the SQL; if putting a certain metric first makes it slow or error, that metric is the main culprit. [[Metric order](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1761532143785779?thread_ts=1761532143.785779&cid=C04S1MSLEAW)] - Temporarily simplify or remove complex metric filters (especially those that require long join paths) and see if performance improves. [[Metric join path](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1770119121028319?thread_ts=1770119121.028319&cid=C04S1MSLEAW)] 4. Look for systemic issues in the model and data source - Open the Data / LDM editor and check for **mapping/validation warnings**; unresolved mapping errors can significantly slow queries. [[LDM mapping impact](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1741731352833269?thread_ts=1741731352.833269&cid=C04S1MSLEAW)] - Verify the data source connection is stable and not intermittently timing out or cancelling queries. [[Connection issues](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1741731352833269?thread_ts=1741731352.833269&cid=C04S1MSLEAW)] 5. Compare with GoodData performance best practices - Use the official performance guide to check database design (partitioning, indexes, materialized views, etc.) and general tuning recommendations. [[Improve performance](https://www.gooddata.com/docs/cloud/connect-data/performance/)] 6. If needed, involve GoodData Support with trace IDs - From failing/slow executions, capture the traceId from the error/DevTools and share it with Support so they can inspect backend logs and confirm whether it’s query complexity, limits, or connection issues. [[Explore timeout](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1721144102677359?thread_ts=1721144102.677359&cid=C04S1MSLEAW); [Performance Q&A](https://gooddataconnect.slack.com/archives/C04S1MSLEAW/p1771251302300799?thread_ts=1771251302.300799&cid=C04S1MSLEAW)] If you can share (outside this chat) one or two specific slow visualizations and their

/debug

SQL, that’s usually enough to pinpoint the exact bottleneck.

Hi Aryan, I see that our AI Assistant provided a good overview of the performance improvement options available to you - Just let us know if you have any other questions