How to Resolve Performance Errors Caused by Dependency Calculations in QuickSight Dashboard?

Q&A
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1

I’m building an inventory aging forecast analysis in QuickSight that calculates aged inventory fees. These fees are only charged for inventory stored for 120, 150, or 180 days, requiring calculations up to day 180 with monthly rolling calculations.

The analysis tracks 6 time points (Day30, Day60, Day90, Day120, Day150, Day180), where each time point calculates 5 aging buckets:

  • 0-90 days

  • 91-180 days

  • 181-270 days

  • 271-365 days

  • 365+ days

Technical Implementation

Calculation Logic:

  • Using nested ifelse logic (avoiding max/min functions as they cause errors in QuickSight)

  • Dependency chain: Day30 → Day60 → Day90 → Day120 → Day150 → Day180

  • Aging rolls over every 90 days, with monthly sales deducted from the highest aging bucket first

Core Issue

When users adjust parameters in the dashboard, the following error occurs:

Error Details:

  • Region: us-east-1

  • Timestamp: 1767753720197

  • RequestId: 08abf0f6-1313-480f-b064-764b32255dd3

The visual displays a calculation error related to the dependency chain.

Technical Constraints

  1. SPICE Limitation: SPICE is enabled but cannot cache parameterized calculation results

  2. Real-time Recalculation: When users adjust parameters, all dependent fields must be recalculated in real-time

  3. Data Volume: The dataset contains multiple ASINs (potentially thousands of records)

Questions for the Community

  1. Performance Optimization: How can I optimize the dependency calculation chain to improve performance?

  2. Alternative Design: Is there a better approach to structure this calculation logic?

  3. Error Prevention: How can I maintain real-time responsiveness while avoiding calculation timeout errors?

    Before Question link: How to resolve errors caused by dependency calculations? - Q&A - Amazon Quick Community

How to resolve errors caused by dependency calculations?
2

I previously received some suggestions to perform calculations on the inventory in the database, but I feel that the Quick Suite dashboard should have more powerful computing capabilities to support dependent calculations.

3

Hi @Haoming

Dependency calculation errors with nested ifelse often arise from runtime recalculation overload on large datasets. Moving non-parameter-dependent logic to data prep maximizes SPICE materialization for better performance.

Shift base aging bucket logic (e.g., categorizing days_since_receipt into 0-90, 91-180 days) to dataset calculated columns during data prep, these materialize in SPICE as static fields, avoiding visual-level recompute.

Precompute aging buckets and time-point simulations upstream in your data pipeline (e.g., Redshift or Athena SQL), ingesting bucketed snapshots monthly into SPICE, this eliminates the dependency chain entirely.

Regrading the error, I would recommend filing a case with AWS Support where we can dive into the details so that we can help you further. Here are the steps to open a support case. If your company has someone who manages your AWS account, you might not have direct access to AWS Support and will need to raise an internal ticket to your IT team or whomever manages your AWS account. They should be able to open an AWS Support case on your behalf. Hope this helps!