What is the main benefit for using the Allow Sparse Row Suppression feature?

What is the main benefit for using the Allow Sparse Row Suppression feature?

• A. Performance improvements for Cube Views that use multiple nested row dimensions
• B. Performance improvements for Cube Views that use dimensions with over 2000 members
• C. Performance improvements that enable the suppression of data below a specified threshold
• D. No noticeable benefit

Answer: (A)

Allow Sparse Row Suppression reduces the work the engine does by hiding rows that don’t contain data. When a cube view has several nested row dimensions, the potential number of rows explodes, but most of those combinations may be empty. Suppressing those empty rows means the system processes and renders far fewer rows, improving performance. This benefit is most noticeable in Cube Views with multiple nested row dimensions, where sparsity is common. It’s not primarily about large member counts or filtering data by a threshold, and a noticeable performance gain is typically observed. So the main benefit is performance improvements for Cube Views that use multiple nested row dimensions.

Allow Sparse Row Suppression reduces the work the engine does by hiding rows that don’t contain data. When a cube view has several nested row dimensions, the potential number of rows explodes, but most of those combinations may be empty. Suppressing those empty rows means the system processes and renders far fewer rows, improving performance. This benefit is most noticeable in Cube Views with multiple nested row dimensions, where sparsity is common. It’s not primarily about large member counts or filtering data by a threshold, and a noticeable performance gain is typically observed. So the main benefit is performance improvements for Cube Views that use multiple nested row dimensions.