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 !!!
