Forum Discussion
Measure Improvement
Hi Community,
Any ideas on how to adjust this step to improve model performance? Loading results is quite slow right now.
Classification =
IF(
[Sales Ranking] > 0.8,
"First",
"Second"
)
Thanks for the reply from Kedar_Pande , Kedar_Pande and lbendlin , please allow me to provide another insight:
Hi, Julia2023
You might also consider adding the following custom column in Power Query:
if [Column1]>=0.8 then "First" else "Second"Power Query loads data into memory when processing, optimising memory usage and reducing memory pressure during subsequent calculations.
Of course, you can also perform performance optimisation checks in the following location within the desktop application:
For further details, please refer to:
Please find the attached pbix relevant to the case.
Of course, if you have any new discoveries or questions, please feel free to get in touch with us.
Best Regards,
Leroy Lu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
5 Replies
Hi Julia2023
Can you please try this one.
Classification =
var SalesRank = [Sales Ranking]
return
IF(SalesRank > 0.8, "First", "Second")
ThanksUse DAX Studio to evaluate the situation and identify the actual culprit (which may be hidden somewhere in your nested measures).
Julia2023
Use Calculated Columns Instead of MeasuresClassification =
IF(
[Sales Ranking] > 0.8,
"First",
"Second"
)
If [Sales Ranking] is based on complex calculations, move those calculations to Power Query or as a calculated column in your data model, if possible, so they don’t get recalculated repeatedly when interacting with the model.💌 If this helped, a Kudos 👍 or Solution mark would be great! 🎉
Cheers,
Kedar
Connect on LinkedInThanks for the reply from Kedar_Pande , Kedar_Pande and lbendlin , please allow me to provide another insight:
Hi, Julia2023
You might also consider adding the following custom column in Power Query:
if [Column1]>=0.8 then "First" else "Second"Power Query loads data into memory when processing, optimising memory usage and reducing memory pressure during subsequent calculations.
Of course, you can also perform performance optimisation checks in the following location within the desktop application:
For further details, please refer to:
Please find the attached pbix relevant to the case.
Of course, if you have any new discoveries or questions, please feel free to get in touch with us.
Best Regards,
Leroy Lu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
To improve performance for this calculation, you can use a calculated column instead of a measure if [Sales Ranking] doesn’t change frequently. Calculated columns are evaluated once when the data is loaded, while measures are recalculated every time you interact with visuals, which can slow down performance.
Here's how you could create it as a calculated column to improve efficiency:
In your table, create a new calculated column with the following formula:
Classification =
IF('YourTable'[Sales Ranking] > 0.8, "First", "Second")
Replace 'YourTable' with the name of the table containing [Sales Ranking].
Additional Tips for Model Performance
Check Data Granularity: If your dataset is very large, try aggregating or summarizing it to reduce the number of rows loaded.
Optimize Data Types: Ensure [Sales Ranking] is of the most efficient data type (e.g., Decimal rather than Text if possible).
Using a calculated column for static classification like this will reduce the need to repeatedly evaluate it in each visual, which can help improve report performance.
Let me know if you need more ideas!
