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You have a Power B1 dataset that contains quarterly sales performance data.
You need to enable managers to review the data in a format that meets the following requirements:
* Is optimized for printing.
* Renders data in Microsoft Excel, Word, PowerPoint, and PDF formats.
What should you create?
Answer : A
You have a source that contains a comumn. The column contains case sensitive date. You have a Power BI semantic model in DirectQuery mode. You connect to the model and discover that it contains undefined values and errors. You need to resolve the issue.
Solution: You add an index key and normalize casing in the data source.
Does this meet the goal?
Answer : A
Adding an index key and normalizing casing in the data source would help resolve issues with undefined values and errors in a case-sensitive column. The index key can provide a unique identifier, and normalizing casing ensures consistency in the data, which would likely prevent the errors you encountered in the Power BI semantic model.
You have a Power BI data model that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys.
* Due Date
* Order Date
* Delivery Date
You need to support the analysis of sales over time based on all three dates at the same time.
Solution: From the Data pane, you rename the date table as Due Date. You use a DAX expression to create Order Date and Deliver Date as calculated tables. You create active relationships between the sales table and each date table.
Does this meet the goal?
Answer : B
Renaming the date table and creating calculated tables for 'Order Date' and 'Delivery Date' with DAX expressions would not fully meet the goal. Power BI only allows one active relationship between two tables at a time. Therefore, you cannot have active relationships between the sales table and all three date tables simultaneously.
Instead, you would typically create one active relationship (e.g., with 'Order Date') and use DAX functions like USERELATIONSHIP to switch between different relationships when needed for analysis. Alternatively, you could use a single date table and create multiple relationships, using inactive relationships and the USERELATIONSHIP function to activate them in specific measures.
Adding an index key and normalizing casing in the data source would help resolve issues with undefined values and errors in a case-sensitive column. The index key can provide a unique identifier, and normalizing casing ensures consistency in the data, which would likely prevent the errors you encountered in the Power BI semantic model.
You have a Power BI data model that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys.
* Due Date
* Order Date
* Delivery Date
You need to support the analysis of sales over time based on all three dates at the same time.
Solution: You create measures that use the USERELATIONSHIP DAX function to filter sales on the inactive relationships between sales table and the date table.
Does this meet the goal?
Answer : A
Adding an index key and normalizing casing in the data source would help resolve issues with undefined values and errors in a case-sensitive column. The index key can provide a unique identifier, and normalizing casing ensures consistency in the data, which would likely prevent the errors you encountered in the Power BI semantic model.
You have a Power BI data model that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys.
* Due Date
* Order Date
* Delivery Date
You need to support the analysis of sales over time based on all three dates at the same time.
Solution: For each date foreign key, you add inactive relationships between the sales table and the date table.
Does this meet the goal?
Answer : B
Simply adding inactive relationships between the sales table and the date table for each date foreign key does not fully meet the goal. While inactive relationships allow for flexibility, they alone do not enable analysis over time based on all three dates simultaneously.
To achieve this, you would need to use DAX functions like USERELATIONSHIP to activate the appropriate relationship in your measures. Without this, the inactive relationships won't be utilized in your calculations, meaning that analysis based on those dates won't work as intended.
