Needing sum work

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Sum and Needing sum work are functions that often founded to be misleading for many Power BI users. As both functions are doing the aggregation, it seems a bit confusing what is the actual difference between these two. There are many blog posts and articles about each function. I always explain the difference with simple demos in my courses and presentations, and people find it easy to understand.

So, I thought better to write it in a blog post for everyone to read. SUM is a simple aggregation function. It summarizes a value based on a filter context. For example, if I have a measure like:. This measure is simply calculating the summarized value of the SalesAmount across the entire fact table when there is no filter selected.

And if I have a filter somewhere in my visualization, then it will calculate the sum of the filtered context. All other aggregation functions are also working the same; Average, Min, Max, Count, and etc. This calculation is considering that we do NOT have a column as a margin in our model, and we do not want to create that column.

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So why you cannot write such a simple statement? As you can see the input is just one column name. It cannot be one column minus another one; that means an expression.

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So, what is the way to do it? One way is to use multiple sum functions, such as below code:. And it would work. However, for long expressions, this way of writing will become hardly readable. If you add one Sum in front of every column name, you may end up with expressions such as below.

Well, there is another way; use SUMX. This function gives you the sum of any expression. Here is the way to use it:. For SUMX to work, you need to specify a table name. When you use SUM you do not need a table name, because one column only belongs to one table.

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But when you use SUMX you may write an expression which uses columns from other tables. In the example for Margin, both columns are coming from the same table; FactInternetSales. So, our expression would be:. How SUMX behind the scene is doing the calculation? SUMX will go through every single record of the input table and run the expression for that record, it stores the result of that into a temporary memory. At the end of parsing the table and calculating all values for every single row, it will summarize them all together, because it is SUMx, releases the temporary memory, and visualize the result.

Iterator functions are looping through all rows in the input table and storing the expression result in a temporary memory storage. At the end they apply the aggregation on the temporary storagerelease the memory usage, and visualize the calculation result.

Another important finding is that it calculates values row by row. If you run SUMX on a very large table with a complex expression, you probably need to wait a bit for to come through. But the hidden gem of using SUMX function is not just the flexibility on the expression, it is also the flexibility on the table input. How we are going to do that? Well, you may say we just use the same SUMX statement that we have used so far, which gives us the result below. But the expression above is not always giving you the total of margin.

If you slice and dice it by a column here is the Needing sum work.

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So, when you are looking at Bachelors education category, the sum of Margin for that is not the total margin, it is just sum of margin for that category. ALL is an interesting function, which I write about it later in another blog post, in the meantime, if I use ALL function to give me the entire table regardless of the filter context, this is what my expression and the result would look like:. How does this work? ALL is a function that returns a table as output. SUMX is a function that gets a table as input.

So they can work with each other nicely! Nesting or cascading functions and tables into each other is something that happens very often in DAX. Because ALL is a function that passes the entire table regardless of the filter context, so, we get the full FactInternetSales table with no filters, and the result would be always the total margin. You may think, what is the usage of such a thing? Well, you can use it to calculate the percentage of the margin for each education category.

Here is how it works:. This can be done with other functions as well. Here, for example, I used the CalculateTable function to do the filtering:. SUMX is a function that you can set an expression and a table as Needing sum work input. Having the ability to change both the expressio, and the table as a filter or something elsemakes this function a generic function to use in DAX. Sum and SumX both are functions calculating aggregation.

However, the SUMX calculates the aggregation on an expression resolved from a table which can be dynamically calculated as well. One thing to remember is that SUMX like any other iterator functions, is consuming temporary memory storage and doing the calculation one row at a time, Needing sum work aggregates it. Do you use SUMX? Let me know where and in which scenarios do you use SUMX for, and ask any questions in the comments below.

Very nice article. I thoroughly enjoyed it…. Thank you. Please explain DAX functions. Very nice article — and clear representation. Thank you, Pretty clear explanation…. I did replicate an excel based simulation sheet in one of my gigs. Hi Willy Yes, it can. You can create a table with possible values. A blog post for that will be coming. Cheers Reza. This has cleared all my doubts. Very well explained. I do follow all your blogs, videos and that help me a lot. Thank you for all your efforts to make people understand things in a easy way. Hi Reza, First of all thank you for this interesting and helpful article.

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Is it true to refuse using SUMX because of memory misuse and its row by row calculation and use calculated column in power query for this reason? So in this case I increase redundancy of my model! SUMX or calculation in power query. Hi Sajjad There is never a definite answer to questions like this. It should be checked case by case and scenario by scenario. SUMX can be slow, but it can be also very effective in some scenarios. Having things pre-calculated is always a good method to speed things up in Power BI.

However, there are scenarios that you need the interaction of user, especially on slicers to affect the way that calculation evaluated. Really appreciate it! And if I have a filter Needing sum work in my visualization, then it will calculate the sum of the filtered context; All other aggregation functions are also working the same; Average, Min, Max, Count, and etc.

Because SUM only accepts a column name as input. Here is the structure of the SUM function; As you can see the input is just one column name. Well, you may say we just use the same SUMX statement that we have used so far, which gives us the result below; But the expression above is not always giving you the total of margin. Summary Sum and SumX both are functions calculating aggregation. Related posts: IF and Filter are Different!

Reza Rad. Reza is also co-founder and co-organizer of Difinity conference in New Zealand. He is the leader of the New Zealand Business Intelligence users group. And He is a Microsoft Certified Trainer. I thoroughly enjoyed it… Loading Thanks for providing the clear understanding Loading Thanks Rasitha! Very helpful article.

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Thank you so much. Thank you; very informative and thought of all questions I would have asked and then some. Great point. The row of course. Fixed now. Best regards Will Loading Cheers Reza Loading Nice explanation. Would be nice to have a video in this topic tho. Thanks very much. Video will be coming. Nice articlevery well explained with right set of examples. SUMX or calculation in power query Loading

Needing sum work

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