dax calculate multiple filters on same column

Find out about what's going on in Power BI by reading blogs written by community members and product staff. You cannot create a physical relationship between Date and Advertising, because the granularity is defined by two columns (Year and Month Number), and there are multiple rows with the same combination of year and month in the Date table. For example, if you have a slicer filtering the brand Proseware, you will see the sales amount of the products Red regardless of the brand, summed to the sales of the entire Contoso brand, regardless of the color but products of Red color and Contoso brand will be summed only once, without duplicating their value. In this example, the expression: DAX. The first is based on FILTER, and it works on any version of DAX. i just have the solution for this case.. Measure 3 = CALCULATE([TotalExaminations];Examinations[exa_StatusID] = "WAI" ||Examinations[exa_StatusID] = "VER" ||Examinations[exa_StatusID] = "APP" ||Examinations[exa_StatusID] = "HEL" ||Examinations[exa_StatusID] = "SCH" ). Evaluates a table expression in a modified filter context. Could someone please help me write it correctly? Read more, This article describes how to use the Group By Columns property to store the slicer selection by using the same column used in a SWITCH function to optimize the query performance. What's the most energy-efficient way to run a boiler? DAX Count with condition | MrExcel Message Board If you are used to the INTERSECT pattern, you might find the TREATAS syntax strange, because you must invert the arguments: the first one is the filter context to read, the second one includes the columns. ALL ( table [column] ), table [column] = <value>. ) How to use filter with multiple values in DAX? My model is attached. In a simple one-to-many relationship, you can just combine different columns into a single one. They are related to the data types and the operation being performed: knowing these details helps you write more robust DAX formulas and avoid errors in comparisons.

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