Marco Russo explains why you might want to use the COMBINEVALUES operator in DAX:

When you import data in a Tabular model, relationships are optimized when they are based on a single column that does not have a high number of unique values. Columns that do have a high number of unique values are known as high cardinality columns. If two tables require two or more columns to define a relationship, it is possible to create a calculated column that concatenates the values of the columns used for the relationship, on both tables. This way, the relationship is based on one single column on each side. However, the resulting calculated column will have a higher cardinality than the original columns, which is not good for performance.

Most of the time, the presence of relationships based on multiple columns suggests that a better denormalization of the model is required to obtain an optimal star schema. Nevertheless, for smaller tables or when it is not possible to apply complex transformations, concatenating columns is the preferred way to obtain the relationships required. When this happens with data loaded in memory, the only concern is the cardinality of the resulting column. However, this is not the main concern in DirectQuery mode.

A calculated column in DirectQuery translates its expression into a native SQL expression. When this is used as a JOIN condition to express the relationship in a Tabular model, this could produce a non-optimal query plan, which could introduce unnecessary slowness in the query execution. For this reason, Microsoft introduced COMBINEVALUES, which is a function expressly designed to optimize relationships based on multiple columns in DirectQuery mode.

Read on for an example.

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