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This addresses a different case: A model needs a calendar that spans minimum and maximum transaction dates. It is not the specific defect in 'Create a many-to-many relationship directly between unrelated fact tables by name'.

This is reasoning supporting the preferred solution 'Model the many-to-many mapping with an explicit bridge and test filter behavior', 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: Direct fact-to-fact ambiguity can double-count or distort totals.

A future test is not yet observed operational evidence. The verification must establish: A salesperson-region test returns the correct nonduplicated mapped sales.

This belongs to a different case: A model needs a calendar that spans minimum and maximum transaction dates. It does not validate the current change.

Approval of a proposed design is not evidence of working behavior. The required observation is: A salesperson-region test returns the correct nonduplicated mapped sales.

This remains unsuitable for the original situation: Direct fact-to-fact ambiguity can double-count or distort totals. It also does not meet the changed need.

This is the already implemented original solution: Model the many-to-many mapping with an explicit bridge and test filter behavior. A bridge makes nonunique mapping relationships deliberate and traceable. It does not itself solve the new requirement.

This observes the original approach but is not an additional action: A salesperson-region test returns the correct nonduplicated mapped sales.

Deleting model keys can invalidate relationships and measures. The proposed shortcut 'Delete the keys used by the relationships to make the field list look cleaner' fails the documented need.

This might be appropriate after a different requirement arises: Report creators request a curated subset of fields for a specific audience. It is not the best initial response to the stated case.

This addresses a separate source situation: Time-intelligence DAX fails because the date field contains gaps and duplicate timestamps. It does not directly satisfy this case's priority. In the current question, this comparison is made against: A clean semantic model has technical surrogate keys that confuse business authors in the Fields pane. Which approach BEST meets the stated Microsoft Power BI requirement?

This addresses a different case: Time-intelligence DAX fails because the date field contains gaps and duplicate timestamps. It is not the specific defect in 'Delete the keys used by the relationships to make the field list look cleaner'.

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Deleting model keys can invalidate relationships and measures.

This is reasoning supporting the preferred solution 'Hide technical keys from Report view without deleting them from the model', but it does not directly name the defect in the proposed shortcut.

This belongs to a different case: Time-intelligence DAX fails because the date field contains gaps and duplicate timestamps. It does not validate the current change. In the current question, this comparison is made against: A clean semantic model has technical surrogate keys that confuse business authors in the Fields pane. After implementing Hide technical keys from Report view without deleting them from the model, which observation BEST demonstrates that the intended result is actually working?

A future test is not yet observed operational evidence. The verification must establish: Business users see descriptive fields while model relationships remain functional.

Approval of a proposed design is not evidence of working behavior. The required observation is: Business users see descriptive fields while model relationships remain functional.

This is the already implemented original solution: Hide technical keys from Report view without deleting them from the model. Hidden fields remain usable for relationships but reduce field-list clutter. It does not itself solve the new requirement.

This remains unsuitable for the original situation: Deleting model keys can invalidate relationships and measures. It also does not meet the changed need.

This observes the original approach but is not an additional action: Business users see descriptive fields while model relationships remain functional.

This might be appropriate after a different requirement arises: The source represents product versions with effective dates. It is not the best initial response to the stated case.

This addresses a separate source situation: A regional sales table uses a mapping bridge where one salesperson can serve multiple regions. It does not directly satisfy this case's priority. In the current question, this comparison is made against: A company's sales model has a product table with repeated ProductIDs and cannot establish a one-to-many relationship. Which approach BEST meets the stated Microsoft Power BI requirement?

Many-to-many may conceal a data-quality problem and create ambiguous totals. The proposed shortcut 'Switch every fact relationship to Many-to-Many without investigating duplicates' fails the documented need.

This is reasoning supporting the preferred solution 'Fix or replace the Products table with a unique ProductID dimension', 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: Many-to-many may conceal a data-quality problem and create ambiguous totals.

This addresses a different case: A regional sales table uses a mapping bridge where one salesperson can serve multiple regions. It is not the specific defect in 'Switch every fact relationship to Many-to-Many without investigating duplicates'.

This belongs to a different case: A regional sales table uses a mapping bridge where one salesperson can serve multiple regions. It does not validate the current change. In the current question, this comparison is made against: A company's sales model has a product table with repeated ProductIDs and cannot establish a one-to-many relationship. After implementing Fix or replace the Products table with a unique ProductID dimension, 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: ProductIDs become unique and an ordinary one-to-many relationship validates.

A future test is not yet observed operational evidence. The verification must establish: ProductIDs become unique and an ordinary one-to-many relationship validates.

This is the already implemented original solution: Fix or replace the Products table with a unique ProductID dimension. The One side of a relationship must have unique keys. It does not itself solve the new requirement.

This observes the original approach but is not an additional action: ProductIDs become unique and an ordinary one-to-many relationship validates.

This remains unsuitable for the original situation: Many-to-many may conceal a data-quality problem and create ambiguous totals. It also does not meet the changed need.