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Historical orders keep their correct customer attributes after a later customer change. That check would be meaningful for the separate case: A customer dimension has slowly changing historical versions and repeat CustomerID business keys. It would not directly verify this scenario's selected implementation: Create an appropriate calculated column or perform the categorization in Power Query.

The axis displays January through December while labels remain readable month names. That check would be meaningful for the separate case: A report's month names sort alphabetically, showing April before January. It would not directly verify this scenario's selected implementation: Create an appropriate calculated column or perform the categorization in Power Query.

The primary measure uses the default path while specialized measures use the alternative key deliberately. That check would be meaningful for the separate case: Two relationships between Customers and Sales are both needed, but Power BI allows only one active filter path. It would not directly verify this scenario's selected implementation: Create an appropriate calculated column or perform the categorization in Power Query.

Using 'Remove the direct fact-to-fact join and use common date and other conformed dimensions' supports the result 'Revenue and returns measures aggregate without artificial row multiplication' for A model designer connects a revenue fact to a returns fact on DateKey alone, causing multiplying row combinations. It does not implement 'Keep the parameter table disconnected and have the selected value read by a measure' or prove 'Changing the discount slicer adjusts the calculation without filtering transaction rows directly' for this question.

'Create and validate the appropriate ProductKey relationship between dimension and fact' is validated when 'Changing Product selection changes only the matching sales amount' for A report shows the same total for every Product because the Products table is disconnected from the sales fact. It does not demonstrate 'Changing the discount slicer adjusts the calculation without filtering transaction rows directly', which requires 'Keep the parameter table disconnected and have the selected value read by a measure'.

A successful 'Create a display hierarchy using the appropriate Date-table columns' would show 'Drill actions move from year to quarter to month in chronological order' for An analyst needs a hierarchy Year-Quarter-Month from a well-defined calendar dimension. This case needs 'Keep the parameter table disconnected and have the selected value read by a measure' and evidence that 'Changing the discount slicer adjusts the calculation without filtering transaction rows directly', not the other outcome.

Changing Product selection changes only the matching sales amount. That check would be meaningful for the separate case: A report shows the same total for every Product because the Products table is disconnected from the sales fact. It would not directly verify this scenario's selected implementation: Keep the parameter table disconnected and have the selected value read by a measure.

Revenue and returns measures aggregate without artificial row multiplication. That check would be meaningful for the separate case: A model designer connects a revenue fact to a returns fact on DateKey alone, causing multiplying row combinations. It would not directly verify this scenario's selected implementation: Keep the parameter table disconnected and have the selected value read by a measure.

Drill actions move from year to quarter to month in chronological order. That check would be meaningful for the separate case: An analyst needs a hierarchy Year-Quarter-Month from a well-defined calendar dimension. It would not directly verify this scenario's selected implementation: Keep the parameter table disconnected and have the selected value read by a measure.

The check for 'Configure explicit sort columns only where there is a stable one-to-one sort mapping' is 'Product categories remain consistently ordered when the report opens' for A categorical ProductName field is accidentally sorted by Amount descending as its natural model sort order. That does not establish 'Product and Date slicers filter SaleAmount summaries without needing fact-to-fact joins'; the stated requirement calls for 'Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior'.

'Keep necessary attributes, hide or remove unsupported payload columns and document the display fields' addresses the mechanism measured by 'The model remains lean while product analysis still groups by meaningful attributes' for A product table has one row per product but includes a complex image URL and unused descriptive text. The current outcome is 'Product and Date slicers filter SaleAmount summaries without needing fact-to-fact joins' after 'Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior', which the distractor leaves unverified.

'Refresh can validate the unique one-side and stores filter their intended transactions' would demonstrate 'Build a unique Store lookup or use an appropriate location surrogate key before creating the relationship' for A store dimension has duplicate StoreID values because source address rows were not normalized, but not 'Product and Date slicers filter SaleAmount summaries without needing fact-to-fact joins'. The latter requires 'Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior' in this scenario.

Refresh can validate the unique one-side and stores filter their intended transactions. That check would be meaningful for the separate case: A store dimension has duplicate StoreID values because source address rows were not normalized. It would not directly verify this scenario's selected implementation: Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior.

The model remains lean while product analysis still groups by meaningful attributes. That check would be meaningful for the separate case: A product table has one row per product but includes a complex image URL and unused descriptive text. It would not directly verify this scenario's selected implementation: Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior.

Product categories remain consistently ordered when the report opens. That check would be meaningful for the separate case: A categorical ProductName field is accidentally sorted by Amount descending as its natural model sort order. It would not directly verify this scenario's selected implementation: Treat Sales as fact and Product and Date as dimensions for filter and aggregation behavior.

Using 'Use the default active path for regular order measures and controlled DAX activation for delivery analysis' supports the result 'The ordinary order total and delivery total respond to their intended respective dates' for An import model has active OrderDate relationship and an inactive DeliveryDate relationship. It does not implement 'Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version' or prove 'Historical orders keep their correct customer attributes after a later customer change' for this question.

'Set measure format and model data categories appropriate to business currency' is validated when 'A monetary card shows the agreed number of decimals while calculations retain precision' for A measure is shown with 12 decimal places even though it represents currency. It does not demonstrate 'Historical orders keep their correct customer attributes after a later customer change', which requires 'Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version'.

A successful 'Extend calendar boundaries to cover fact dates and necessary comparison periods' would show 'Time-intelligence calculations have calendar dates for the required prior periods' for A generated Date table starts after the earliest recorded transaction date and misses prior-year comparisons. This case needs 'Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version' and evidence that 'Historical orders keep their correct customer attributes after a later customer change', not the other outcome.

A monetary card shows the agreed number of decimals while calculations retain precision. That check would be meaningful for the separate case: A measure is shown with 12 decimal places even though it represents currency. It would not directly verify this scenario's selected implementation: Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version.

Time-intelligence calculations have calendar dates for the required prior periods. That check would be meaningful for the separate case: A generated Date table starts after the earliest recorded transaction date and misses prior-year comparisons. It would not directly verify this scenario's selected implementation: Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version.

The ordinary order total and delivery total respond to their intended respective dates. That check would be meaningful for the separate case: An import model has active OrderDate relationship and an inactive DeliveryDate relationship. It would not directly verify this scenario's selected implementation: Use a unique version-level surrogate key in the dimension and map facts to the applicable historical version.

The check for 'Create or identify MonthNumber and apply Sort by Column to MonthName' is 'The axis displays January through December while labels remain readable month names' for A report's month names sort alphabetically, showing April before January. That does not establish 'Revenue and returns measures aggregate without artificial row multiplication'; the stated requirement calls for 'Remove the direct fact-to-fact join and use common date and other conformed dimensions'.

'Remove or constrain redundant paths and use intentional single-direction star relationships' addresses the mechanism measured by 'Filter propagation is unambiguous and regional sales reconcile to source totals' for The model contains two potentially ambiguous bidirectional paths from Region to Sales through different tables. The current outcome is 'Revenue and returns measures aggregate without artificial row multiplication' after 'Remove the direct fact-to-fact join and use common date and other conformed dimensions', which the distractor leaves unverified.

'Selecting one salesperson filters the sales and commission measures consistently' would demonstrate 'Create separate one-to-many relationships from a conformed Salesperson dimension to both facts' for A salesperson lookup filters a sales fact but also needs to filter a commission fact with the same salesperson key, but not 'Revenue and returns measures aggregate without artificial row multiplication'. The latter requires 'Remove the direct fact-to-fact join and use common date and other conformed dimensions' in this scenario.

Selecting one salesperson filters the sales and commission measures consistently. That check would be meaningful for the separate case: A salesperson lookup filters a sales fact but also needs to filter a commission fact with the same salesperson key. It would not directly verify this scenario's selected implementation: Remove the direct fact-to-fact join and use common date and other conformed dimensions.

Filter propagation is unambiguous and regional sales reconcile to source totals. That check would be meaningful for the separate case: The model contains two potentially ambiguous bidirectional paths from Region to Sales through different tables. It would not directly verify this scenario's selected implementation: Remove the direct fact-to-fact join and use common date and other conformed dimensions.

The axis displays January through December while labels remain readable month names. That check would be meaningful for the separate case: A report's month names sort alphabetically, showing April before January. It would not directly verify this scenario's selected implementation: Remove the direct fact-to-fact join and use common date and other conformed dimensions.

Using 'Create a display hierarchy using the appropriate Date-table columns' supports the result 'Drill actions move from year to quarter to month in chronological order' for An analyst needs a hierarchy Year-Quarter-Month from a well-defined calendar dimension. It does not implement 'Keep necessary attributes, hide or remove unsupported payload columns and document the display fields' or prove 'The model remains lean while product analysis still groups by meaningful attributes' for this question.

'Keep a primary active relationship and use a specific inactive relationship in targeted DAX when appropriate' is validated when 'The primary measure uses the default path while specialized measures use the alternative key deliberately' for Two relationships between Customers and Sales are both needed, but Power BI allows only one active filter path. It does not demonstrate 'The model remains lean while product analysis still groups by meaningful attributes', which requires 'Keep necessary attributes, hide or remove unsupported payload columns and document the display fields'.

A successful 'Create a one-to-many relationship from unique Product to repeating Sales keys' would show 'A product slicer filters the correct matching sales rows without duplicate-dimension-key errors' for A sales fact has repeated ProductKey values while a product dimension contains one row per ProductKey. This case needs 'Keep necessary attributes, hide or remove unsupported payload columns and document the display fields' and evidence that 'The model remains lean while product analysis still groups by meaningful attributes', not the other outcome.

The primary measure uses the default path while specialized measures use the alternative key deliberately. That check would be meaningful for the separate case: Two relationships between Customers and Sales are both needed, but Power BI allows only one active filter path. It would not directly verify this scenario's selected implementation: Keep necessary attributes, hide or remove unsupported payload columns and document the display fields.

Drill actions move from year to quarter to month in chronological order. That check would be meaningful for the separate case: An analyst needs a hierarchy Year-Quarter-Month from a well-defined calendar dimension. It would not directly verify this scenario's selected implementation: Keep necessary attributes, hide or remove unsupported payload columns and document the display fields.

A product slicer filters the correct matching sales rows without duplicate-dimension-key errors. That check would be meaningful for the separate case: A sales fact has repeated ProductKey values while a product dimension contains one row per ProductKey. It would not directly verify this scenario's selected implementation: Keep necessary attributes, hide or remove unsupported payload columns and document the display fields.