Microsoft Fabric Analytics Engineer Associate DP-600
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with creating a reusable Power BI data source (.pbids) file for a project that requires frequent updates and adaptability across multiple reports. The solution must minimize manual updates, support dynamic data source connections, and be easily shareable among team members. Considering these requirements, which of the following approaches should you take? (Choose one option.)
A
Create a new report in Power BI Desktop, add the data source, and save the entire report as a .pbix file. This method ensures all data and visualizations are stored together but may not be the most efficient for reusing the data source across different reports.
B
In Power BI Desktop, create a new report, add the desired data source, and save only the data source as a .pbids file. This approach allows for the data source to be reused in multiple reports, with the ability to parameterize connections for adaptability.
C
Manually create a folder on your local machine, copy the data source files into it, and then import these files into Power BI Desktop as needed. This method lacks efficiency and does not support dynamic data source connections.
D
Use Azure Data Factory to create a data pipeline that imports the data source and automatically generates a new Power BI report. While this method automates data import, it does not directly address the need for a reusable .pbids file.