With which query considerations can you optimize the query performance? (3)

Question

Options

• AUse characteristic filters that overlap
• BUse include functions in the restricted key figures
• CUse mandatory characteristics value variables
• DUse fewer drill-down characteristics in the initial view
• EUse exclude functions in the restricted key figures

• A
  10% (5)
• B
  6% (3)
• C
  84% (43)

Explanation

Optimizing query performance in OLAP/reporting systems (such as SAP BW) hinges on reducing data volume early and limiting initial rendering complexity.

Why C, D, and E are correct:

• (C) Mandatory characteristic value variables force users to supply filter values before query execution, so the database processes only the relevant data subset rather than the full dataset.
• (D) Fewer drill-down characteristics in the initial view reduces the number of aggregation levels the engine must compute on startup, keeping the initial result set lean.
• (E) Exclude functions in restricted key figures narrow the data scope at the key figure level by removing unwanted values, reducing the rows the engine must read and aggregate.

Why A and B are wrong:

• (A) Overlapping characteristic filters create redundant logic the system must resolve, adding processing overhead rather than reducing it.
• (B) Include functions in restricted key figures expand or enumerate the values the engine must actively retrieve and process, which is generally heavier than an exclude pattern that simply filters out a smaller unwanted set.

Memory tip: Think "Restrict, Reduce, Remove" - Mandatory variables restrict input, fewer drill-downs reduce initial rendering, and exclude functions remove unwanted data. All three shrink the workload before the engine does heavy lifting.

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