High number of metrics in the dashboard

Question & Answer
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I am trying to convert approximately 300 metrics, which involve 5,500 lines of Redshift SQL code, into a dashboard.

I am concerned about whether QuickSight is capable of handling such complex metric calculations, and if this will affect the performance of the dashboard. I cannot perform these calculations in the backend because I want to provide users with the flexibility to select their desired date range and multiple warehouses.

Could you please advise on the following:

  1. Can QuickSight handle the processing of such a large and complex set of metric calculations (300 metrics, 5,500 lines of SQL) without impacting the dashboard’s performance?
  2. What are the best practices or recommendations for handling complex calculations in a QuickSight dashboard, where users need the flexibility to filter data based on different parameters?
  3. Are there any specific techniques or approaches I should consider to optimize the performance and ensure a seamless user experience, given the scale and complexity of the metrics involved?
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Hi @emehta and welcome to the QuickSight community!

In terms of QuickSight’s ability to handle metrics of your capacity, does your concern come from behavior you’ve received while testing out specific calculations?
From my experience using large datasets with complex calculations, I have not encountered any processing errors.
Some recommendations for handling these calculations, you could try out:

  • Build some of your calculated fields at the dataset level, this can reduce load times
  • Use custom SQL on ingestion to run some calculations within the query
  • Setting up Parameters and utilizing them in controls
  • Try to limit the number of visuals on a sheet if it’s a more complex calculation that’s occurring. You can setup navigation actions to help guide you between sheets if you do need to split them up.
  • Setting your dataset to SPICE can greatly help with load times as well

Another thing you could explore would be Materialized views in Redshift.

Overall, it’s hard to say what would be the best practice for your specific case without testing to see how the performance is. Then if you are encountering errors, we can assist in a more defined way!

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Thank you for that information Brett. We are currently in the process of building out the dashboard and want to be pro active about any measures that need to be taken. Our concern stems from the fact that most of the metrics are interdependent on each other and contribute towards the calculation of the final (about 80) metrics. Since there are ratios involved as well, we cant calculate them in the dataset!

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Hi @emehta,
I wanted to follow up and see if you had any additional questions prior to me closing out this topic.

If we do not hear back within the next 3 business days, I’ll go ahead and close.

Thank you!

5

Hi @emehta,
Since we haven’t heard back, I’ll go ahead and close out this topic. However, if you have any additional questions, feel free to create a new post in the community.

Thank you!