Forum Discussion
export from visual table
- 5 months ago
Power BI visuals often show formatted values (e.g., 2 decimals), but calculations use the full precision value.
When exporting:
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CSV may contain more decimal precision than shown
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Excel recalculates totals using raw numbers
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Result → small differences in totals
Best practice to fix is to use same decimal number for both the measure and used field values used within it.
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- 5 months ago
Hey Gianluigi ,
Most commonly, this happens because of rounding. Power BI calculates using full precision in the background, even if the visual shows only two decimal places. When you export to CSV, the full precision values are exported, and Excel recalculates the total using those exact numbers. With a large number of rows, small decimal differences can add up.
If that’s the case, you can fix it by rounding the value directly in your DAX measure so both the visual and the export use the same precision.
Another common reason is when the column is a measure (like an average, ratio, or DISTINCTCOUNT). In those cases, Power BI recalculates the total instead of summing the visible rows. So when you sum the exported rows in Excel, it may not match and that’s expected behavior.
So it’s not a bug, but depending on the scenario, it can usually be controlled with rounding or by understanding how the measure total is calculated.
Hey Gianluigi ,
Yes, this actually happens more often than people expect, especially when you’re dealing with large datasets. You’re definitely not alone in seeing this.
When you export a visual table from Power BI to CSV and then total it in Excel, small differences can appear for a few common (and totally normal) reasons.
First, the most common cause is rounding vs. full precision.
In Microsoft Power BI, the numbers you see in the visual are often rounded for display purposes for example, shown with 2 decimal places. But internally, Power BI stores and calculates using the full precision of the number.
When you export to CSV:
- The full precision values are exported.
- Excel then recalculates totals using those full precision numbers.
So what happens is:
- The visual total is calculated using precise internal values.
- In Microsoft Excel, if you sum the exported rows (especially if they’re displayed as rounded values), you may get a slightly different total.
- With thousands (or millions) of rows, those tiny decimal differences add up.
That’s usually the number one reason.
The second common reason is how totals are calculated for measures.
If your column in the visual is actually a measure (not a simple column from your table), Power BI does something important:
The total is not always the “sum of the visible rows.”
Instead, Power BI recalculates the measure again in the total context.
For example:
- A ratio
- An average
- A DISTINCTCOUNT
- A weighted calculation
- Any DAX measure with logic
In those cases:
- The total in the visual is mathematically correct based on the DAX logic.
- But in Excel, when you sum the exported rows, you’re just adding the visible results — which may not equal the recalculated total.
This difference becomes more noticeable when the row count is large.
Another factor can be data reduction or export type.
Depending on whether you exported:
- “Summarized data”
- Or “Underlying data”
You may not be exporting exactly what you think you are. If it’s summarized data, the aggregation might already be applied before export.
There’s also something called floating-point precision. Both Power BI and Excel use floating-point arithmetic. When you’re working with very large volumes of numbers especially decimals tiny precision differences can accumulate and show up in totals.
So to answer your question directly:
Yes, this has happened to many others. It’s expected behavior in most cases, not a bug.
If this solved your issue, please mark it as the solution so others can find it easily.
If it helped, a quick 👍 Kudos is always appreciated it helps highlight useful answers for the community.
Thanks for being part of the discussion !!!
- Gianluigi5 months agoHelper II
Hello MohdZaid_ , I understand that it's normal behavior. So there's no solution then? Thanks
- MohdZaid_5 months agoSuper User
Hey Gianluigi ,
Most commonly, this happens because of rounding. Power BI calculates using full precision in the background, even if the visual shows only two decimal places. When you export to CSV, the full precision values are exported, and Excel recalculates the total using those exact numbers. With a large number of rows, small decimal differences can add up.
If that’s the case, you can fix it by rounding the value directly in your DAX measure so both the visual and the export use the same precision.
Another common reason is when the column is a measure (like an average, ratio, or DISTINCTCOUNT). In those cases, Power BI recalculates the total instead of summing the visible rows. So when you sum the exported rows in Excel, it may not match and that’s expected behavior.
So it’s not a bug, but depending on the scenario, it can usually be controlled with rounding or by understanding how the measure total is calculated.