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Anonymous
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## SUMX vs SUM | COUNTX vs COUNT | AVERAGEX vs Average

Hi all,

I have watched so many Youtube videos and blog posts about the difference between the aggregating vs itterative functions, but am still failing to grasp the concepts here.

Can someone please, in the most basic way possible, explain when to use each? What the difference is? How to apply the itterative functions correctly? I see way too much of this, and quite frankly, am discouraged that I'm not able to get over this hurdle.

Would appreciate any input. Thank you.

2 ACCEPTED SOLUTIONS
Frequent Visitor
Helper II

Hi @Anonymous

Please don't get disheartened as sometimes it takes time to grasp concepts.

Lets take an example of SUM and SUMX. Suppose you have a Sales table in which Total Price is given to you at which the product was sold. Now if you have to find out the Total Revenue that were made then you can use the function SUM as follows -

Total Revenue = SUM('Sales'[Total Price])

But now suppost that in the Sales table, instead of giving Total Price, there are two columns - Quantity and Unit Price. Now if you have to find out the Total Revenue then if we just see the maths behind it then we will have to multiply Quantity with Unit Price to get the Total Price for the transaction and then we will have to sum this Total Price obtained from the measure to get the Total Revenue. Now this is a two step process, first we have to multiple the Quantity with Unit Price and then once this is done for all transactions then we will have to add them. SUM function is not having the ability to do this two fold process and therefore SUMX comes into play. Here is how you can create a measure using SUMX-

Total Revenue = SUMX ('Sales', 'Sales'[Quantity] * 'Sales'[Unit Price])

The second part of sumx where expression is written helps in performing calculation for each row present in the dataset and then once that is done the Sum of the end result of that expression is done.

Hope this clarifies.

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Thanks

2 REPLIES 2
Helper II

Hi @Anonymous

Please don't get disheartened as sometimes it takes time to grasp concepts.

Lets take an example of SUM and SUMX. Suppose you have a Sales table in which Total Price is given to you at which the product was sold. Now if you have to find out the Total Revenue that were made then you can use the function SUM as follows -

Total Revenue = SUM('Sales'[Total Price])

But now suppost that in the Sales table, instead of giving Total Price, there are two columns - Quantity and Unit Price. Now if you have to find out the Total Revenue then if we just see the maths behind it then we will have to multiply Quantity with Unit Price to get the Total Price for the transaction and then we will have to sum this Total Price obtained from the measure to get the Total Revenue. Now this is a two step process, first we have to multiple the Quantity with Unit Price and then once this is done for all transactions then we will have to add them. SUM function is not having the ability to do this two fold process and therefore SUMX comes into play. Here is how you can create a measure using SUMX-

Total Revenue = SUMX ('Sales', 'Sales'[Quantity] * 'Sales'[Unit Price])

The second part of sumx where expression is written helps in performing calculation for each row present in the dataset and then once that is done the Sum of the end result of that expression is done.

Hope this clarifies.

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Thanks

Frequent Visitor

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