Forum Discussion
Performance Concerns with Manual Row-Level Table and SWITCH Function
Hi bdpr_95
That’s a great point, and I understand your concern about the SWITCH logic still being present. To better assist your current setup and explore if we can streamline it differently maybe even eliminate the SWITCH entirely, I would really appreciate if you could share a small sample of your dataset.
Could you provide:
-
A few rows from your base table showing Column1, Column2, and Column3
-
A list or table of how you want the final visual to look (with expected values for Measure 1, 2, 3, etc.)
This will help me tailor the solution specifically to your logic, and potentially offer a more scalable approach for the 36+ possibilities you're managing.
How to provide sample data in the Power BI Forum - Microsoft Fabric Community-
Hi bdpr_95
That’s a great point, and I understand your concern about the SWITCH logic still being present. To better assist your current setup and explore if we can streamline it differently maybe even eliminate the SWITCH entirely, I would really appreciate if you could share a small sample of your dataset.
Could you provide:
-
A few rows from your base table showing Column1, Column2, and Column3
-
A list or table of how you want the final visual to look (with expected values for Measure 1, 2, 3, etc.)
This will help me tailor the solution specifically to your logic, and potentially offer a more scalable approach for the 36+ possibilities you're managing.
How to provide sample data in the Power BI Forum - Microsoft Fabric Community
Hi v-aatheeque , I’ve already done that in message 5. I didn’t provide an example with data, but it’s clear that to get my final output, I need to have in my first column the names I want to display in my visual, and in the second column the metrics. These metrics, in certain cases, can be filtered using a column from the fact table (e.g., Column2 = 1), while in other cases it might be necessary to filter a different column (e.g., Column3 = 45).
Hi bdpr_95
To provide a solution that scales effectively (especially with 36+ conditions), we want to make sure without sample data or a clear mapping between your condition logic and the metric names.
For aunderstanding , could you provide:
- A few rows of example data from your base table (Column1, Column2, and Column3 ) just with dummy values.
- A clearer structure or example of the 36 conditions you're currently managing.
- An overview of how each measure interacts with your data model.
This will help us recommend a clean and scalable approach that avoids maintaining 36+ separate measures.
Hi bdpr_95
As earlier requested to provide further we need :-
A few sample rows from your base table (Column1, Column2, Column3) with dummy values.
-
A clear example or outline of the 36 conditions you’re using.
-
How each measure connects to your data model.
This will allow us to suggest a cleaner approach without needing to maintain so many separate measures.
looking forward for your response !!-