Microsoft Power BI PL-300 Exam Questions 2025

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Our PL-300 exam questions provide authentic, up-to-date questions for the Microsoft Power BI Data Analyst certification, carefully reviewed by certified experts. Each set includes accurate answers, detailed explanations, and clarifications on incorrect options to help you master data modeling, visualization, and analytics. With free demo questions and our online exam simulator, Cert Empire ensures youโ€™re fully prepared to pass the PL-300 exam with confidence.

Exam Questions

Question 1

You have a Power Bl workspace that contains a dataset. a report, and a dashboard. The following groups have access: โ€ข External users can access the dashboard. โ€ข Managers can access the dashboard and a manager-specific report. โ€ข Employees can access the dashboard and a row-level security (RLS) constrained report. You need all users, including the external users, to be able to tag workspace administrators if they identify an issue with the dashboard. The solution must ensure that other users see the issues that were raised. What should you use?
Options
A: subscriptions
B: comments
C: alerts
D: chat in Microsoft Teams
Show Answer
Correct Answer:
comments
Explanation
The comments feature in the Power BI service is designed for collaboration directly on dashboards and reports. It allows all users with access, including external guest users, to add comments. Crucially, it supports "@" mentions, which can be used to tag and notify workspace administrators about an issue. The comment thread is visible to everyone who can view the dashboard, ensuring that other users can see the issues that were raised. This directly meets all the requirements of the scenario.
Why Incorrect Options are Wrong

A. subscriptions: Subscriptions are used to schedule and email snapshots of reports and dashboards to users. They do not provide a mechanism for feedback or collaborative issue tracking.

C. alerts: Data alerts are automated notifications triggered when data in a dashboard tile crosses a predefined threshold. They are not a tool for users to manually report issues.

D. chat in Microsoft Teams: While Power BI content can be shared in Teams for discussion, this creates a separate communication channel. The comments feature is a more integrated, native solution within the Power BI service itself.

References

1. Microsoft Learn. (2023). Add comments to dashboards and reports in the Power BI service.

Section: "Add a general comment" and "Comment on a specific visual"

Content: This document explicitly states, "You can add comments to an entire dashboard... You can also @mention others to pull them into the conversation." It confirms that comments are a collaborative feature visible to those with access.

2. Microsoft Learn. (2023). Email subscriptions for Power BI reports and dashboards.

Section: "Subscribe to a report or dashboard"

Content: This source details the functionality of subscriptions, which is to "receive an email with a snapshot of the report or dashboard." This confirms it is a content delivery system, not a communication tool.

3. Microsoft Learn. (2023). Data alerts in the Power BI service.

Section: "Set data alerts in the Power BI service"

Content: This document explains that alerts are used to "get notified when data in your dashboards changes above or below limits you set." This confirms alerts are for automated data monitoring, not user-initiated communication.

Question 2

You have a report in Power Bl named report1 that is based on a shared dataset. You need to minimize the risk of data exfiltration for report1. The solution must prevent other reports from being affected. What should you do?
Options
A: Clear Allow recipients to share your dashboard and Allow users to build new content using the underlying datasets for the dataset.
B: Select the Allow end users to export both summarized and underlying data from the service or Report Server Export data option for the report.
C: Select the Don't allow end users to export any data from the service or Report Server Export data option for the report.
D: Apply row-level security (RLS) to the shared dataset.
Show Answer
Correct Answer:
Select the Don't allow end users to export any data from the service or Report Server Export data option for the report.
Explanation
To minimize data exfiltration for a single report without affecting other reports using the same shared dataset, you must apply a report-level setting. The "Export data" option in the report's settings allows you to control data export specifically for that report. Selecting "Don't allow end users to export any data" directly prevents users from exporting summarized or underlying data from visuals in report1, thereby mitigating the risk of data exfiltration. This change is isolated to report1 and does not alter the shared dataset or any other reports connected to it.
Why Incorrect Options are Wrong

A. Modifying dataset permissions affects all reports and users connected to that shared dataset, violating the requirement that other reports should not be affected.

B. This option explicitly allows data export, which increases the risk of data exfiltration, directly contradicting the goal of the question.

D. Row-level security (RLS) is applied at the dataset level, which would affect all reports using that dataset. It restricts data access but does not prevent the export of visible data.

References

1. Microsoft Learn. (2023). Change report settings in the Power BI service.

Section: "Export data"

Content: This document details the report-level settings for data export. It explicitly lists the option to set export permissions to "None," which "prevents your report readers from exporting any data from your report." This confirms it is a report-specific control.

2. Microsoft Learn. (2024). Build permission for shared datasets.

Section: "Ways to get Build permission"

Content: This document clarifies that "Build permission is a dataset-level permission." Modifying it, as suggested in option A, would impact anyone trying to build content from the shared dataset, thus affecting more than just report1.

3. Microsoft Learn. (2024). Row-level security (RLS) with Power BI.

Section: "Set up RLS"

Content: The documentation explains that RLS is configured on the model (dataset) in Power BI Desktop and then managed in the Power BI service. This confirms RLS is a dataset-level feature and would apply to all reports using that dataset.

Question 3

HOTSPOT You have a Power Bl report. You have the following tables. PL-300 exam question You have the following DAX measure. PL-300 exam question PL-300 exam question

Show Answer
Correct Answer:

HTTPS://KXBJSYUHCEGGSYVXDKOF.SUPABASE.CO/STORAGE/V1/OBJECT/PUBLIC/FILE-IMAGES/PL-300/PAGE_311_IMG_2.JPG


Explanation

The DAX measure [Accounts] is designed to count the number of unique accounts. A standard implementation for this would be DISTINCTCOUNT(Balances[AccountID]). This measure operates within the filter context provided by the visual.

  • Day Level: When the table visual is at the day level, the filter context for the measure is a single day. The measure will count the distinct accounts that have a record in the Balances table for that specific day, which correctly represents the number of accounts live on that day.
  • Month and Year Level: When the context is expanded to a month or a year, the DISTINCTCOUNT function will count every unique account that had a balance record on at least one day within that period. It does not ensure the account was active for every single day of the period. An account active for only one day in a year will be counted the same as an account active for all 365 days. Therefore, the measure does not show accounts that were live throughout the entire month or year.
References

Microsoft Corporation. (n.d.). DISTINCTCOUNT function (DAX). Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/dax/distinctcount-function-dax

This document states that the function "counts the number of distinct values in a column." When applied over a date range, it counts all distinct values that appear at any point within that range.

Microsoft Corporation. (n.d.). Understanding filter context. Power BI Documentation. Retrieved from https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-evaluation-context#filter-context

This resource explains how visuals, such as a table grouped by a date hierarchy, create a filter context that constrains DAX calculations to a subset of data (e.g., a specific day, month, or year).

Russo, M., & Ferrari, A. (2019). The Definitive Guide to DAX: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel (2nd ed.). Microsoft Press.

Chapter 4, "Evaluation Contexts," explains in detail how filter context is applied at different granularities and how measures like DISTINCTCOUNT operate within that context. It confirms that a distinct count over a period includes items present at any point in the period, not necessarily throughout.

Question 4

HOTSPOT You have a Power Bl report named Orders that supports the following analysis: โ€ข Total sales over time โ€ข The count of orders over time โ€ข New and repeat customer counts The data model size is nearing the limit for a dataset in shared capacity. The model view for the dataset is shown in the following exhibit. PL-300 exam question PL-300 exam question

Show Answer
Correct Answer:

YES

NO

NO

Explanation

Summarizing Orders (Yes): This is a standard data reduction technique. By summarizing or aggregating the Orders table (which is likely at a transaction line level), you reduce the total number of rows. A new table grouped by CustomerID, OrderID, and OrderDate would contain one row per order instead of one row per product line within an order. This significantly reduces the model size. To support the "Total sales over time" analysis, a new column for the total sales amount would be created during this summarization process. The other analysesโ€”counting orders and analyzing customersโ€”remain possible because OrderID, CustomerID, and OrderDate are retained.


Removing CustomerID (No): Removing the CustomerID column from the Orders fact table would break the relationship with the Customers dimension table. While this would reduce the model size, it would make it impossible to perform the "New and repeat customer counts" analysis, as there would be no way to link an order to a specific customer.


Removing UnitPrice and Discount (No): These columns are necessary to calculate the Total Sales measure (e.g., Sales = Quantity * UnitPrice * (1 - Discount)). Removing them would make it impossible to support the "Total sales over time" analysis, even though it would reduce the model size.

References

Microsoft Power BI Documentation: In the guidance on data reduction techniques for Import modeling, summarizing data is a key strategy. The documentation states, "Use Power Query to group by columns, and aggregate your data... It can result in a significant data reduction." This directly supports the first statement, as summarizing is a valid and effective method to reduce model size while maintaining analytical capability by pre-aggregating measures. (See: Microsoft Docs, Power BI guidance, Data reduction techniques for Import modeling).

Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (3rd ed.). Wiley. Chapter 2 discusses the grain of a fact table. The process described in the first statement is equivalent to raising the grain of the fact table from an individual transaction line to the order header. This is a fundamental technique in dimensional modeling to manage performance and data volume for large datasets. Removing foreign keys (Statement 2) or measure source columns (Statement 3) violates basic dimensional modeling principles for supporting the required analyses.

Question 5

You have the Power Bl model shown in the following exhibit. PL-300 exam question There are four departments in the Departments table. You need to ensure that users can see the data of their respective department only. What should you do?
Options
A: Create a row-level security (RLS) role for each department, and then define the membership of the role.
B: Create a DepartmentID parameter to filter the Departments table.
C: To the ConfidentialData table, add a calculated measure that uses the currentgroup DAX function.
D: Create a slicer that filters Departments based on DepartmentID.
Show Answer
Correct Answer:
Create a row-level security (RLS) role for each department, and then define the membership of the role.
Explanation
The requirement is to restrict data access so that users can only view data corresponding to their specific department. This is the primary use case for Row-Level Security (RLS) in Power BI. RLS is implemented by creating roles within the Power BI model. For each role, a DAX filter expression is defined on a table (in this case, the Departments table). When a user assigned to a specific role accesses the report in the Power BI service, this DAX filter is automatically applied, restricting the rows of data they can see throughout the entire model. This method enforces security at the data model level.
Why Incorrect Options are Wrong

B. A parameter is a user-controlled input for interactive analysis, not a security feature. A user could easily change the parameter value to view data from other departments.

C. The CURRENTGROUP DAX function is used within grouping functions like SUMMARIZECOLUMNS to perform calculations on grouped data; it is not related to user-based security.

D. A slicer is a visual filter on the report canvas that users can freely interact with. It does not enforce security, as a user could modify or remove the slicer.

References

1. Microsoft Learn. (2024). Restrict data access with row-level security (RLS) for Power BI. Microsoft Power BI Documentation. Retrieved from https://learn.microsoft.com/en-us/power-bi/enterprise/service-admin-rls.

Reference Details: The section "Define roles and rules in Power BI Desktop" explicitly states, "You can define roles and rules within Power BI Desktop. When you publish to Power BI, it also publishes the role definitions... To define security roles, follow these steps. 1. Import data into your Power BI Desktop report, or configure a DirectQuery connection. ... 2. From the Modeling tab, select Manage Roles." This directly supports the process described in option A.

2. Microsoft Learn. (2024). Implement row-level security. PL-300: Design and build a data model in Power BI learning path. Retrieved from https://learn.microsoft.com/en-us/training/modules/design-build-tabular-model-power-bi/7-implement-row-level-security.

Reference Details: This official PL-300 courseware notes, "Row-level security (RLS) is a Power BI feature that can be used to restrict data access for given users. Filters restrict data access at the row level, and you can define filters within roles... You will implement RLS by creating one or more roles. A role has a unique name in the model, and it will typically include one or more rules."

3. Microsoft Learn. (2024). Row-level security (RLS) guidance in Power BI Desktop. Power BI Guidance Documentation. Retrieved from https://learn.microsoft.com/en-us/power-bi/guidance/rls-guidance.

Reference Details: The section "Implement RLS" details the process: "In Power BI Desktop, you can create a role by navigating to the Modeling ribbon and selecting Manage roles. In the Manage roles window, you can create, modify, or delete roles... You add a rule to a table by using a DAX expression that must return a TRUE or FALSE value." This confirms that creating roles and defining rules is the correct procedure.

Question 6

HOTSPOT You have a column named UnitslnStock as shown in the following exhibit. PL-300 exam question UnitsInStock has 75 non-null values, of which 51 are unique. Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point. PL-300 exam question

Show Answer
Correct Answer:

WHEN A TABLE VISUAL IS CREATED IN A REPORT AND UNITSINSTOCK IS ADDED TO THE VALUES, THERE WILL BE 75 ROWS IN THE TABLE.

CHANGING THE SUMMARIZE BY SETTING OF THE UNITSINSTOCK COLUMN, AND THEN ADDING THE COLUMN TO A TABLE VISUAL, WILL REDUCE THE NUMBER OF ROWS IN THE TABLE VISUAL.

Explanation

The UnitsInStock column has its Summarize by property set to None. When a numeric column with this setting is added to a table visual, Power BI does not aggregate the data. Instead, it displays each individual value on a separate row. Since the column has 75 non-null values, the table will display 75 rows.


Changing the Summarize by setting from 'None' to an aggregation function (such as Sum, Average, or Count) alters this behavior. When the column is subsequently added to a table, Power BI will perform the specified calculation and display a single, aggregated result (assuming no other grouping columns are present). This changes the output from 75 individual rows to a single summary row, thus reducing the number of rows.

References

Microsoft Power BI Documentation: In the "Use aggregation in Power BI Desktop" article, it states: "If you set the summarization to Do not summarize, then whenever you add that column to a visual, Power BI will simply show each of its values." This confirms that without summarization, all individual values are listed.

Source: Microsoft Learn, Power BI Documentation, "Use aggregation (sum, average, etc.) in Power BI Desktop," Section: "Change the aggregation type."

Microsoft Power BI Documentation: The default behavior for numeric fields is aggregation. As explained in the documentation, "When you add a numeric field...to a visual in a Power BI report, it's aggregated by default. It might be a sum, average, count...". Enabling summarization (by changing it from 'None') causes the data to be aggregated into fewer rows, typically one if it's the only field in the values well.

Source: Microsoft Learn, Power BI Documentation, "Intro to aggregations in Power BI," Section: "Why use aggregations?"

Question 7

DRAG DROP You plan to create a report that will display sales data from the last year for multiple regions You need to restrict access to individual rows of the data on a per region-basis by using roles. Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. PL-300 exam question

Show Answer
Correct Answer:

IMPORT THE DATA TO POWER BI DESKTOP.

CREATE A ROLE DEFINITION.

PUBLISH THE REPORT.

ASSIGN USERS TO THE ROLE.

Explanation

The process of implementing Row-Level Security (RLS) in Power BI follows a specific workflow. First, you must bring your data into Power BI Desktop. Once the data model is available, you define the security rules by creating roles and applying DAX filter expressions to the tables. After defining the roles within the .pbix file, the report must be published to the Power BI service. The final step, which can only be done in the service, is to navigate to the dataset's security settings and assign specific users or groups to the roles you created, thereby activating the security restrictions for them.

References

Microsoft. (2024). Row-level security (RLS) with Power BI. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/power-bi/enterprise/service-admin-rls.

Details: The "Set up roles in Power BI Desktop" section outlines the initial steps: "1. Import data into your Power BI Desktop report... 2. From the Modeling tab, select Manage Roles." This supports the first two steps in the sequence. The "Manage security on your model" section details the subsequent actions: "...you need to publish your report to the Power BI service... In the Power BI service, you can assign members to the role." This confirms the final two steps.

Question 8

You import a Power Bl dataset that contains the following tables: โ€ข Date โ€ข Product โ€ข Product Inventory The Product inventory table contains 25 million rows. A sample of the data is shown in the following table. PL-300 exam question The Product Inventory table relates to the Date table by using the DateKey column. The Product inventory table relates to the Product table by using the ProductKey column. You need to reduce the size of the data model without losing information. What should you do?
Options
A: Change Summarization for DateKey to Don't Summarize.
B: Change the data type of UnitCost to Integer.
C: Remove the relationship between Date and Product Inventory.
D: Remove MovementDate.
Show Answer
Correct Answer:
Remove MovementDate.
Explanation
The Product Inventory table contains both a DateKey column (used for the relationship to the Date table) and a MovementDate column. Since the DateKey already links each record to a specific date in the Date dimension table, the MovementDate column is redundant. All date-related information (year, month, day, etc.) can be retrieved via the relationship. Removing the unnecessary MovementDate column from the 25-million-row fact table is a primary optimization technique. This action significantly reduces the model's memory footprint by eliminating a high-cardinality column without any loss of analytical information.
Why Incorrect Options are Wrong

A. Changing summarization is a metadata setting that affects default report behavior; it does not reduce the data model's storage size.

B. Changing the UnitCost data type to Integer would truncate decimal values (e.g., 12.02 becomes 12), resulting in a loss of information.

C. Removing the relationship between the tables would break the ability to analyze inventory by date, which is a critical loss of analytical capability.

References

1. Microsoft Learn. (2023). Data reduction techniques for Import modeling. In Power BI guidance.

Reference: Under the section "Remove unnecessary columns," the documentation states, "Columns that don't serve a purpose should be removed from your model... It's a best practice to remove any columns that aren't used for relationships, measures, or displaying in visuals." In this scenario, MovementDate is redundant because DateKey serves the relationship purpose.

2. Microsoft Learn. (2023). Understand star schema and the importance for Power BI. In Power BI guidance.

Reference: This document describes that fact tables should contain foreign keys (like DateKey) and numeric measures. Descriptive attributes (like a full date) should reside in the related dimension tables. The presence of MovementDate in the fact table violates this principle when a proper Date dimension exists, confirming its redundancy.

Question 9

HOTSPOT You plan to create a Power Bl dataset to analyze attendance at a school. Data will come from two separate views named View1 and View? in an Azure SQL database. View1 contains the columns shown in the following table. PL-300 exam question View2 contains the columns shown in the following table. PL-300 exam question The views can be related based on the Class ID column. Class ID is the unique identifier for the specified class, period, teacher, and school year. For example, the same class can be taught by the same teacher during two different periods, but the class will have a different class ID. You need to design a star schema data model by using the data in both views. The solution must facilitate the following analysis: The count of classes that occur by period The count of students in attendance by period by day The average number of students attending a class each month In which table should you include the Teacher First Name and Period Number fields? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. PL-300 exam question

Show Answer
Correct Answer:

TEACHER FIRST NAME: TEACHER DIMENSION

PERIOD NUMBER: ATTENDANCE FACT


Explanation

In dimensional modeling, the goal is to create a star schema consisting of a central fact table and multiple surrounding dimension tables.

  1. Fact Tables: Contain quantitative measures and foreign keys to dimension tables. The Attendance data from View2 is transactional and forms the basis of the Attendance fact table.
  2. Dimension Tables: Contain descriptive, categorical attributes that describe the factual data. Attributes like teacher names, class subjects, and period times are used to slice and dice the measures in the fact table.

Teacher First Name is a descriptive attribute of a teacher entity. The best practice is to create a separate Teacher dimension containing fields like Teacher ID, Teacher First Name, and Teacher Last Name. This avoids data redundancy and organizes the model logically.

Period Number is required to analyze attendance counts by period. For the Attendance fact table to be filterable by period, it must contain a key related to the period. Since the source data for the facts (View2) already includes Period Number, it should be included in the Attendance fact table as a foreign key that links to a Period dimension.

References

Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (3rd ed.). Wiley.

Chapter 2, "Retail Sales": This chapter introduces the core concepts of fact and dimension tables. It explains that descriptive textual attributes (like a teacher's name) belong in dimension tables, while numeric keys that connect facts to dimensions belong in the fact table (p. 25-29).

Microsoft Power BI Documentation. (2023). "Understand star schema and the importance for Power BI."

Section: "Fact tables": The documentation states, "The fact table contains dimension key columns that relate to dimension tables...". This confirms that keys needed for slicing data, like Period Number, must be present in the fact table to link to their respective dimension tables.

Section: "Dimension tables": This section clarifies that dimension tables "store the attributes that describe your business entities," which directly applies to placing Teacher First Name in a Teacher dimension.

Question 10

You have more than 100 published datasets. Ten of the datasets were verified to meet your corporate quality standards. You need to ensure that the 10 verified datasets appear at the top of the list of published datasets whenever users search for existing datasets. What should you do?
Options
A: Publish the datasets in an app.
B: Promote the datasets.
C: Feature the dataset on the home page.
D: Certify the datasets.
Show Answer
Correct Answer:
Certify the datasets.
Explanation
Certification is the designated process in Power BI for marking datasets as authoritative and trustworthy, confirming they meet an organization's quality standards. Certified datasets are given the highest priority and a special badge in discovery experiences, such as the Data hub and when connecting to data from Power BI Desktop. This ensures they appear at the top of any list when users search for datasets, directly fulfilling the requirement. Promotion is a lower level of endorsement and ranks below certified content.
Why Incorrect Options are Wrong

A. Publish the datasets in an app: This bundles content for consumption but does not affect the ranking of datasets in discovery lists.

B. Promote the datasets: While promotion increases visibility, certification provides a higher level of endorsement and a higher rank in search results, aligning with "corporate quality standards."

C. Feature the dataset on the home page: This provides a shortcut on the Power BI Home page but does not influence the order of datasets in search results.

References

1. Microsoft Learn. (2023, October 24). Endorsement: Promote and certify Power BI content. In the "How endorsement works" section, it states, "Certified content is ranked first in lists and search results, and is marked with a certification badge." It also notes, "Certification is a bigger deal than promotion. You can certify content only if your Power BI admin has configured and enabled certification for your organization." This directly supports that certification is the correct action for datasets verified against corporate standards to achieve top ranking.

2. Microsoft Learn. (2023, October 24). Enable content certification. In the "Set up content certification" section, it explains, "Certification is a way to highlight quality content. To ensure that only authoritative content gets certified, Power BI admins decide who can certify content." This aligns with the scenario's need to elevate datasets that meet "corporate quality standards."

3. Microsoft Learn. (2023, October 24). Data discovery using the data hub. The article illustrates how endorsed datasets are displayed prominently in the Data hub, stating, "The list of datasets shows you the workspace they reside in, as well as whether they're certified or promoted." This confirms that certification directly impacts visibility in user search experiences.

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