Hi @dting
When dealing with visualization complexity, several factors can affect the latency of loading pivot tables, including:
- Measures and Dimensions: The number and complexity of measures and dimensions directly impact the processing time. Complex calculations, multiple measures, and high cardinality dimensions (dimensions with many unique values) can increase the load time as Quick Sight needs to process more data.
- Filters and Slicing: Applying filters, especially those that are computationally intensive (like filters on calculated fields), can slow down loading times. The more filters and conditions you apply, the more processing Quick Sight has to do, which can increase latency.
- Visual Complexity: The complexity of the visual itself—such as the number of rows and columns in a pivot table, or the use of conditional formatting and calculated fields—can affect performance. More complex visuals require more processing power and time to render.
Please refer the below documentation this might be helpful for you.