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Microsoft PL-300 Exam Questions
- Topic 1: Prepare the data: Getting data from data sources and cleaning the data are focal points of this topic. It also explains transforming and loading the data.
- Topic 2: Model the data: It delves into designing and implementing a data model. The sub-topic of creating model calculations by using DAX is also present. Moreover, it discusses optimizing model performance.
- Topic 3: Visualize and analyze the data: Creating reports, enhancing reports for usability and storytelling, and identifying patterns and trends are sub-topics of this exam topic.
- Topic 4: Manage and secure Power BI: In this topic, the focal point is on creating and managing workspaces.
Free Microsoft PL-300 Exam Actual Questions
Note: Premium Questions for PL-300 were last updated On Jul. 28, 2025 (see below)
You have a Power BI report that uses a dataset based on an Azure Analysis Services live connection.
You need to ensure that users can use Q&A from the Power BI service for the dataset.
What should you do?
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 create a parameter named DataSourceExcel that holds the file name and location of a Microsoft Excel data source.
You need to update the query to reference the parameter instead of multiple hard-coded copies of the location within each query definition.
Solution: In the Power Query M code, you replace references to the Excel file with DataSourceExcel.
Does this meet the goal?
Instead modify the source step of the queries to use DataSourceExcel as the file path.
Note: Parameterising a Data Source could be used in many different use cases. From connecting to different data sources defined in Query Parameters to load different combinations of columns.
https://www.biinsight.com/power-bi-desktop-query-parameters-part-1/
You have a Microsoft Power BI report. The size of PBIX file is 550 MB. The report is accessed by using an App workspace in shared capacity of powerbi.com.
The report uses an imported dataset that contains one fact table. The fact table contains 12 million rows. The dataset is scheduled to refresh twice a day at 08:00 and 17:00.
The report is a single page that contains 15 AppSource visuals and 10 default visuals.
Users say that the report is slow to load the visuals when they access and interact with the report.
You need to recommend a solution to improve the performance of the report.
What should you recommend?
DirectQuery: No data is imported or copied into Power BI Desktop.
Import: The selected tables and columns are imported into Power BI Desktop. As you create or interact with a visualization, Power BI Desktop uses the imported data.
Benefits of using DirectQuery
There are a few benefits to using DirectQuery:
DirectQuery lets you build visualizations over very large datasets, where it would otherwise be unfeasible to first import all the data with pre-aggregation.
Underlying data changes can require a refresh of data. For some reports, the need to display current data can require large data transfers, making reimporting data unfeasible. By contrast, DirectQuery reports always use current data.
The 1-GB dataset limitation doesn't apply to DirectQuery.
https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-use-directquery
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 scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a clustered bar chart that contains a measure named Salary as the value and a field named Employee as the axis. Salary is present in the data as numerical amount representing US dollars.
You need to create a reference line to show which employees are above the median salary.
Solution: You create a percentile line by using the Salary measure and set the percentile to 50%.
Does this meet the goal?
The 50th percentile is also known as the median or middle value where 50 percent of observations fall below.
https://dash-intel.com/powerbi/statistical_functions_percentile.php
Each employee has one manager as shown in the ParentEmployeelD column,
All reporting paths lead to the CEO at the top of the organizational hierarchy.
You need to create a calculated column that returns the count of levels from each employee to the CEO.
Which DAX expression should you use?
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