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jan0204
Frequent Visitor

Help with waterfall chart

I am relatively a newbie to powerbi, and first time working with waterfall chart in powerbi. I am working on variance data. This data shows the Total Variance (measure) between last year vs current year by supplier or category. The category waterfall chart displays the correct Total Variance, however the supplier variance chart is displaying a much higher Total Variance. I am not sure where I am wrong. Pretty much all the parameters are the same. The only thing I am changing is category to supplier. Data is fairly huge. I am sharing screen shots here.

 

jan0204_0-1716257474768.pngjan0204_1-1716257506442.png

Thank you,

JJ

1 REPLY 1
Anonymous
Not applicable

Hi @jan0204 ,

In the absence of data, it is difficult to give specific solutions.

Please try the following:

1. Check Data Aggregation: Ensure that the measure for Total Variance is correctly aggregating data at the supplier level. Sometimes, aggregation issues can lead to inflated totals. Review the measure formula to confirm it's aggregating as expected.

 

2. Review Data Model Relationships: If your data model involves multiple tables, ensure that the relationships between the tables (especially those involving the supplier dimension) are correctly configured. Incorrect or missing relationships can lead to unexpected results in your visualizations.

 

3. Filter Context: Verify if there are any filters applied at the page, report, or visual level that might be influencing the Total Variance calculation differently when switching from category to supplier. Sometimes, hidden or unintentional filters can affect the results.

 

4. Data Type and Format: Double-check that the data types and formats for the supplier and category fields are consistent and correctly set up. Mismatches in data types or formats can sometimes lead to aggregation issues.

 

Best regards,
Community Support Team_Binbin Yu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

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