DAX function for highlights latest value in each month
I want to hightlights new product in my table that never been sold before in previous month.
DAX function for highlights latest value in each month
I want to hightlights new product in my table that never been sold before in previous month.
DAX function for highlights latest value in each month
I want to hightlights new product in my table that never been sold before in previous month.
DAX function for highlights latest value in each month
I want to hightlights new product in my table that never been sold before in previous month.
DAX function for highlights latest value in each month
I want to hightlights new product in my table that never been sold before in previous month.
Filter outside RELATEDTABLE without ignoring table relationship
I’m new to DAX. Please bear with me.
I have a called Sales Transaction grouped by Location and Customer Code (and may expand the grouping based on user). I need to set a boolean status for months after the transaction.
Filter outside RELATEDTABLE without ignoring table relationship
I’m new to DAX. Please bear with me.
I have a called Sales Transaction grouped by Location and Customer Code (and may expand the grouping based on user). I need to set a boolean status for months after the transaction.
DAX query doesn’t take into consideration working days
I need help in writing a DAX query which works out the difference between two dates(feedback receipt date and acknowledgement date) and minus any working days. e.g. if feedback date was the 12th and acknowledgement date was the 19th, the working days to acknowledge will be 5 days, minus Saturday and Sunday.
Row level security with multiple columns in Power BI
In order to be able to give access level to each user, I did the following.
I have a main database in which there are columns such as buyer and seller, transaction volume, transaction value,…
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how do i separate the positive and negative values in one column into separate columns using DAX
I want to separate the values in one column into separate columns so that the negative values will be on one column and the positive in one column. see sample dataset below