If you are used to virtual relationships in DAX (see Handling Different Granularities in DAX), you probably use the following pattern relatively often:
[Filtered Measure] := CALCULATE ( <target_measure>, FILTER ( ALL ( <target_granularity_column> ), CONTAINS ( VALUES ( <lookup_granularity_column> ), <lookup_granularity_column>, <target_granularity_column> )
) )
In the new DAX available in Excel 2016*, Power BI Desktop, and Analysis Services 2016, you can use a simpler syntax, which offers a minimal performance improvement and is much more readable:
[Filtered Measure] := CALCULATE ( <target_measure>, INTERSECT ( ALL ( <target_granularity_column> ), VALUES ( <lookup_granularity_column> )
) )
You can find a longer explanation of this new pattern and download some examples in the new article Physical and Virtual Relationships in DAX, on SQLBI web site.
Evaluates an expression in a context modified by filters.
CALCULATE ( <Expression> [, <Filter> [, <Filter> [, … ] ] ] )
Returns a table that has been filtered.
FILTER ( <Table>, <FilterExpression> )
Returns all the rows in a table, or all the values in a column, ignoring any filters that might have been applied.
ALL ( [<TableNameOrColumnName>] [, <ColumnName> [, <ColumnName> [, … ] ] ] )
Returns TRUE if there exists at least one row where all columns have specified values.
CONTAINS ( <Table>, <ColumnName>, <Value> [, <ColumnName>, <Value> [, … ] ] )
When a column name is given, returns a single-column table of unique values. When a table name is given, returns a table with the same columns and all the rows of the table (including duplicates) with the additional blank row caused by an invalid relationship if present.
VALUES ( <TableNameOrColumnName> )
Returns the rows of left-side table which appear in right-side table.
INTERSECT ( <LeftTable>, <RightTable> )