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This remains unsuitable for the original situation: Sorting changes display order rather than creating rule-based flags. It also does not meet the changed need.

This observes the original approach but is not an additional action: Rows over 500 are marked premium and other rows follow the rule.

This is the already implemented original solution: Add a conditional column implementing the accepted price rule. Conditional columns derive attributes from explicit row-level tests. It does not itself solve the new requirement.

This might be appropriate after a different requirement arises: DiscountPercent is added to the source. It is not the best initial response to the stated case.

This addresses a separate source situation: A base cleaned Orders query must feed both retail and wholesale reporting tables without redoing the source cleanup. It does not directly satisfy this case's priority.

Appending rows performs no per-row multiplication. The proposed shortcut 'Use Append Queries to calculate an arithmetic product' fails the documented need.

This is reasoning supporting the preferred solution 'Add a Power Query custom column for Quantity multiplied by UnitPrice', but it does not directly name the defect in the proposed shortcut.

This addresses a different case: A base cleaned Orders query must feed both retail and wholesale reporting tables without redoing the source cleanup. It is not the specific defect in 'Use Append Queries to calculate an arithmetic product'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Appending rows performs no per-row multiplication.

This belongs to a different case: A base cleaned Orders query must feed both retail and wholesale reporting tables without redoing the source cleanup. It does not validate the current change.

A future test is not yet observed operational evidence. The verification must establish: NetAmount matches known row samples and is numeric.

Approval of a proposed design is not evidence of working behavior. The required observation is: NetAmount matches known row samples and is numeric.

This remains unsuitable for the original situation: Appending rows performs no per-row multiplication. It also does not meet the changed need.

This observes the original approach but is not an additional action: NetAmount matches known row samples and is numeric.

This is the already implemented original solution: Add a Power Query custom column for Quantity multiplied by UnitPrice. Custom columns calculate row-level expressions during data preparation. It does not itself solve the new requirement.

Currency is not an appropriate Boolean type. The proposed shortcut 'Set the source field to Currency and rely on display formatting' fails the documented need.

This addresses a separate source situation: A company stores Product, Category, and Brand repeated across every order line. It does not directly satisfy this case's priority. In the current question, this comparison is made against: An old application exports OrderFlag values Y and N, while a new semantic model needs true Boolean values. Which approach BEST meets the stated Microsoft Power BI requirement?

This might be appropriate after a different requirement arises: The source adds a third value U for unknown. It is not the best initial response to the stated case.

This addresses a different case: A company stores Product, Category, and Brand repeated across every order line. It is not the specific defect in 'Set the source field to Currency and rely on display formatting'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Currency is not an appropriate Boolean type.

This is reasoning supporting the preferred solution 'Replace or map Y and N to True and False and assign Logical type', but it does not directly name the defect in the proposed shortcut.

A future test is not yet observed operational evidence. The verification must establish: All Y records become true and N records false after refresh.

This belongs to a different case: A company stores Product, Category, and Brand repeated across every order line. It does not validate the current change. In the current question, this comparison is made against: An old application exports OrderFlag values Y and N, while a new semantic model needs true Boolean values. After implementing Replace or map Y and N to True and False and assign Logical type, which observation BEST demonstrates that the intended result is actually working?

Approval of a proposed design is not evidence of working behavior. The required observation is: All Y records become true and N records false after refresh.

This remains unsuitable for the original situation: Currency is not an appropriate Boolean type. It also does not meet the changed need.

This is the already implemented original solution: Replace or map Y and N to True and False and assign Logical type. Explicit mapping yields reliable logical values for filtering. It does not itself solve the new requirement.

This observes the original approach but is not an additional action: All Y records become true and N records false after refresh.

This might be appropriate after a different requirement arises: Analysts later want total stock units per product as well. It is not the best initial response to the stated case.

Deduplication at product grain loses valid location rows. The proposed shortcut 'Remove duplicates on ProductID before counting locations' fails the documented need.

This addresses a separate source situation: An order-source XML file has repeated LineItem nodes that must become fact rows. It does not directly satisfy this case's priority.

This is reasoning supporting the preferred solution 'Group by ProductID and calculate a distinct location count', but it does not directly name the defect in the proposed shortcut.

This addresses a different case: An order-source XML file has repeated LineItem nodes that must become fact rows. It is not the specific defect in 'Remove duplicates on ProductID before counting locations'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Deduplication at product grain loses valid location rows.