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Product familiarity is not evidence of suitability. The actual defect in this proposal is: Pivot would create the opposite shape from the requested tidy fact table.

This addresses a different case: A Power Query dataset needs Column A as headers and has one junk metadata row at the top. It is not the specific defect in 'Use Pivot to spread monthly rows into even more columns'.

This is reasoning supporting the preferred solution 'Unpivot the monthly columns to Month and Value rows', but it does not directly name the defect in the proposed shortcut.

Approval of a proposed design is not evidence of working behavior. The required observation is: The output has one Month column and one numeric Value column.

This belongs to a different case: A Power Query dataset needs Column A as headers and has one junk metadata row at the top. It does not validate the current change.

A future test is not yet observed operational evidence. The verification must establish: The output has one Month column and one numeric Value column.

This observes the original approach but is not an additional action: The output has one Month column and one numeric Value column.

This is the already implemented original solution: Unpivot the monthly columns to Month and Value rows. Unpivot converts repeated categorical headers into a tidy attribute-value pair. It does not itself solve the new requirement.

This remains unsuitable for the original situation: Pivot would create the opposite shape from the requested tidy fact table. It also does not meet the changed need.

This might be appropriate after a different requirement arises: Auditors later require a normalized event table for trend analysis. It is not the best initial response to the stated case.

This addresses a separate source situation: An analyst must retain every sale even when a matching product master row is missing. It does not directly satisfy this case's priority.

Unpivoting an existing attribute cannot create the required cross-tab. The proposed shortcut 'Unpivot Status when Status is already stored as the desired attribute' fails the documented need.

This is reasoning supporting the preferred solution 'Group or pivot status values into columns with an appropriate aggregation', but it does not directly name the defect in the proposed shortcut.

This addresses a different case: An analyst must retain every sale even when a matching product master row is missing. It is not the specific defect in 'Unpivot Status when Status is already stored as the desired attribute'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Unpivoting an existing attribute cannot create the required cross-tab.

Approval of a proposed design is not evidence of working behavior. The required observation is: The result shows a separate status count for each IncidentID.

This belongs to a different case: An analyst must retain every sale even when a matching product master row is missing. It does not validate the current change.

A future test is not yet observed operational evidence. The verification must establish: The result shows a separate status count for each IncidentID.

This remains unsuitable for the original situation: Unpivoting an existing attribute cannot create the required cross-tab. It also does not meet the changed need.

This is the already implemented original solution: Group or pivot status values into columns with an appropriate aggregation. Pivot can turn distinct row values into column headings. It does not itself solve the new requirement.

This observes the original approach but is not an additional action: The result shows a separate status count for each IncidentID.

Deduplication discards valid transactions instead of summing them. The proposed shortcut 'Remove duplicate CustomerID rows and keep only the first sale' fails the documented need.

This might be appropriate after a different requirement arises: The report later needs monthly customer totals. It is not the best initial response to the stated case.

This addresses a separate source situation: A sales fact contains both a date-time timestamp and a reporting requirement grouped by calendar day. It does not directly satisfy this case's priority.

This is reasoning supporting the preferred solution 'Use Group By CustomerID with Sum over the sales amount', but it does not directly name the defect in the proposed shortcut.

This addresses a different case: A sales fact contains both a date-time timestamp and a reporting requirement grouped by calendar day. It is not the specific defect in 'Remove duplicate CustomerID rows and keep only the first sale'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Deduplication discards valid transactions instead of summing them.

A future test is not yet observed operational evidence. The verification must establish: The grouped table's customer totals match independently calculated source sums.

Approval of a proposed design is not evidence of working behavior. The required observation is: The grouped table's customer totals match independently calculated source sums.

This belongs to a different case: A sales fact contains both a date-time timestamp and a reporting requirement grouped by calendar day. It does not validate the current change.

This observes the original approach but is not an additional action: The grouped table's customer totals match independently calculated source sums.

This is the already implemented original solution: Use Group By CustomerID with Sum over the sales amount. Power Query Group By aggregates multiple rows into a specified grain. It does not itself solve the new requirement.

This remains unsuitable for the original situation: Deduplication discards valid transactions instead of summing them. It also does not meet the changed need.