DAX Functions - All vs Allselected (Which one do you use?)
In this video Mitchell discusses the difference between the ALL function and the ALLSELECTED function and how each of them serve to solve different analytical r
In this video, Mitchell explores the distinction between the ALL and ALL SELECTED functions, explaining their unique applications for various analytical needs. The discussion provides clarity on the appropriate circumstances for using each function, helping viewers make informed decisions when handling their data. Mitchell’s goal is to aid in understanding which function is most suitable given a specific scenario, thus enhancing viewers’ analytical proficiency.
DAX (Data Analysis Expressions) is a formula language used in Power BI to create custom calculations on data models. Two of these functions are ALL and ALLSELECTED.
- ALL: The ALL function in DAX is a function that is used to clear or ignore any filters that might be applied to a table or a column in a table. When you use ALL in a function, you're essentially asking Power BI to forget about any context and consider all the data in the specified table or column. It returns all the rows in a table, or all the values in a column, ignoring any filters that might have been applied.
For example:
CALCULATE(SUM([Sales]), ALL('Product'))
This expression would calculate the sum of all sales across all products, ignoring any current product filter context.
- ALLSELECTED: The ALLSELECTED function is a variant of the ALL function. It returns all the rows in a table, or all the values in a column, while retaining the context of the user's selections, rather than ignoring all filters. Essentially, it preserves the filters that are currently applied due to user interaction on the report, but removes all other filters.
For example:
CALCULATE(SUM([Sales]), ALLSELECTED('Product'))
This expression would calculate the sum of all sales for the products that are currently selected in the report, ignoring other filter contexts but preserving user selections.
These two functions are used for different types of analysis in Power BI, and understanding when to use each one is key to effectively manipulating and interpreting your data.