How to reduce performance of visual for color conditioning formatting features

[Kella]

There are matrix table visual need to apply the color code to the data table.

From the figure show the different performance duration with and without apply color code conditioning formatting.

It is have any suggestion to reduce the performance duration at the same time apply the color code conditioning formatting.

Thanks for help on this.

[Adamboer]

There are a few ways to improve performance of visuals with color conditioning formatting:

1. Limit the amount of data displayed in the visual by using filters or slicers. This will reduce the amount of data that needs to be processed, and can improve overall performance.

2. Consider using a different visual that doesn't require color conditioning formatting, such as a table or a chart.

3. Try simplifying the color conditioning formatting by using fewer colors or applying the formatting to a smaller subset of data. This can reduce the amount of processing required for the visual.

4. Reduce the number of conditional formatting rules in the visual. Each rule adds additional processing time, so limiting the number of rules can improve performance.

5. Consider upgrading your hardware or using a faster internet connection if possible, as this can also help improve performance.

[edhans]

Conditional formatting is just another value for the visual to render then apply, so the performance of it will depend on the DAX you have written in your base measures to determine how to return the values. And it depends on how you are telling it to render the format too - using another measure, using a range of numbers, or using a fixed color metric.

We will need a lot more info to assist.

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[Kella]

Thanks @edhans 

This is the color measure that applied to the PBI report as local measure.Is there a difference in term of performance between local and SSAS measure since this measure added as a local.

_Sample = 
Var Sales1 = [Adv_Sales (% TN v TTL)]
Var Sales2 = 
    CALCULATE([Adv_Sales (% TN v TTL)],
    ALL('STATE'), ALL('SALES_CENTER'), ALL('PRODUCT')
    )
Return
IF(Sales1 > Sales2, "GREEN", "RED")

[edhans]

There is no difference assuming it isn't a composite model. If it is a thin report (Live connection) it will be the same.

The key then is what is the [Adv_Sales (% TN v TTL)] measure? That has to be calculated twice, once within the filter context of the report, and then with the filters removed from 3 tables.

And that is 1 time per "Cell". So a 12 month bar chart is 12 times. A matrix with 4 columns and 30 rows is 120 times. The engine greatly optimizes this and takes advantage of the cache, but of that measure is slow, then the conditional formatting will be doubly slow.

[Kella]

Thanks @edhans 

The [Adv_Sales (% TN v TTL)] - This measure taking 15 seconds to populate the data.Can you help to redefine this measure.

[edhans]

15 seconds is an extraordinarily long time. That is the measure you need to optimize before trying to optimize conditional formatting that references that measure twice, once with and once without certian filters removed. The one with filters removed could take considerably more time if it has to process more of the fact table.