Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a data source that contains a column. The column contains case sensitive data. 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 normalize casing in the source query or Power Query Editor. Does this meet the goal?

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A. Yes Normalizing casing (e.g., converting all text to uppercase or lowercase) ensures that identical values with different casing are treated consistently, thereby resolving problems like mismatched joins, filters, or unexpected undefined values that arise from case-sensitive comparisons in the data source or model. Performing this transformation in Power Query Editor or the source query ensures data consistency before it's used in the Power BI semantic model.

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B. No Normalizing casing directly addresses the root cause of case sensitivity issues by making data consistent, which will resolve errors and undefined values stemming from such inconsistencies.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might h

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