Which is true about creating a context filter for a crosstab report using a dimensional data source?

Question

Options

• Ait changes the measure values and the items in the rows and columns
• Bit is applied after aggregation and changes the rows and columns
• Cit changes the measure values and suppresses zeros
• Dit filters only the measure values, not the items in the rows and columns

• A
  5% (2)
• B
  3% (1)
• C
  78% (29)
• D
  14% (5)

Explanation

Option C is correct because in a dimensional (OLAP) data source, a context filter acts as a slicer that adjusts the measure values displayed in the crosstab cells while also suppressing members whose values become zero as a result - the dimensional structure (rows and columns) is driven by the cube hierarchy, not rewritten by the filter, but empty/zero results are hidden.

Why the distractors are wrong:

• A is wrong because the filter does not directly rewrite which dimension members appear as row/column headers - it only affects the values, with zero suppression as a side effect.
• B is wrong because describing it as "applied after aggregation" that "changes rows and columns" conflates it with a detail or post-aggregation filter; context filters in dimensional sources don't restructure the axes that way.
• D is almost right but incomplete - it correctly notes that row/column items aren't directly changed, but it ignores the zero-suppression behavior, making C the more accurate and complete answer.

Memory tip: In dimensional sources, think "context = values + vanishing zeros." The cube's axes stay intact, but cells filtered to zero disappear - the filter reshapes what you see without rebuilding the dimensional structure.

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