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This remains unsuitable for the original situation: Integer type cannot preserve the intended calendar dates. It also does not meet the changed need.

This is the already implemented original solution: Use Change Type with Locale for the correct regional date format. Parsing with the appropriate locale avoids reversing or invalidating day and month. It does not itself solve the new requirement.

This observes the original approach but is not an additional action: The transformed field recognizes 31 December 2025 correctly.

Fact duplicates may be valid line items and need different checks. The proposed shortcut 'Remove all duplicates in the Sales fact by InvoiceNumber without checking transaction grain' fails the documented need.

This might be appropriate after a different requirement arises: Customers can legitimately hold multiple addresses over time. It is not the best initial response to the stated case.

This addresses a separate source situation: A country column uses US, USA, and United States to represent one market. It does not directly satisfy this case's priority.

This is reasoning supporting the preferred solution 'Assess duplicate keys and remove or reconcile duplicate customer rows', but it does not directly name the defect in the proposed shortcut.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Fact duplicates may be valid line items and need different checks.

This addresses a different case: A country column uses US, USA, and United States to represent one market. It is not the specific defect in 'Remove all duplicates in the Sales fact by InvoiceNumber without checking transaction grain'.

A future test is not yet observed operational evidence. The verification must establish: CustomerKey is unique and row counts agree with the trusted source.

This belongs to a different case: A country column uses US, USA, and United States to represent one market. It does not validate the current change.

Approval of a proposed design is not evidence of working behavior. The required observation is: CustomerKey is unique and row counts agree with the trusted source.

This remains unsuitable for the original situation: Fact duplicates may be valid line items and need different checks. It also does not meet the changed need.

This observes the original approach but is not an additional action: CustomerKey is unique and row counts agree with the trusted source.

This is the already implemented original solution: Assess duplicate keys and remove or reconcile duplicate customer rows. A one-side dimension needs one row per relationship key. It does not itself solve the new requirement.

This might be appropriate after a different requirement arises: Some keys also have inconsistent capitalization. It is not the best initial response to the stated case.

This addresses a separate source situation: A delivery feed has unusual extreme travel durations, and managers want to know if those are anomalies. It does not directly satisfy this case's priority.

Report visuals do not repair nonmatching join values. The proposed shortcut 'Add a new chart without touching either key' fails the documented need.

This addresses a different case: A delivery feed has unusual extreme travel durations, and managers want to know if those are anomalies. It is not the specific defect in 'Add a new chart without touching either key'.

This is reasoning supporting the preferred solution 'Apply Trim to the text keys before creating the merge', but it does not directly name the defect in the proposed shortcut.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Report visuals do not repair nonmatching join values.

Approval of a proposed design is not evidence of working behavior. The required observation is: Previously unmatched keys match after trimming and the exception count drops.

A future test is not yet observed operational evidence. The verification must establish: Previously unmatched keys match after trimming and the exception count drops.

This belongs to a different case: A delivery feed has unusual extreme travel durations, and managers want to know if those are anomalies. It does not validate the current change.

This observes the original approach but is not an additional action: Previously unmatched keys match after trimming and the exception count drops.

This is the already implemented original solution: Apply Trim to the text keys before creating the merge. Invisible whitespace can prevent equality matches on otherwise identical text. It does not itself solve the new requirement.

This remains unsuitable for the original situation: Report visuals do not repair nonmatching join values. It also does not meet the changed need.

This addresses a separate source situation: A customer extract has duplicate records for the same customer key because of an accidental export join. It does not directly satisfy this case's priority.

Blanket deletion may erase legitimate return transactions. The proposed shortcut 'Delete every negative row without checking whether it represents an approved return' fails the documented need.

This might be appropriate after a different requirement arises: The data owner defines a new returns transaction type. It is not the best initial response to the stated case.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Blanket deletion may erase legitimate return transactions.

This is reasoning supporting the preferred solution 'Profile the quantity distribution and flag invalid or return-specific records for business review', but it does not directly name the defect in the proposed shortcut.

This addresses a different case: A customer extract has duplicate records for the same customer key because of an accidental export join. It is not the specific defect in 'Delete every negative row without checking whether it represents an approved return'.