PL-300 Practice Questions 2026: Free Power BI Sample (with Answers)
Eleven free PL-300 sample questions with full answer explanations covering Power Query, data modeling, DAX, visuals, and deployment. Each question matches the style and difficulty of the real Microsoft exam.
Table of Contents
About the PL-300 Exam
The Microsoft PL-300: Power BI Data Analyst Associate is the most popular Power BI certification, validating your ability to enable businesses to maximize their data assets. The exam evaluates four core competencies: preparing, modeling, visualizing, and deploying data solutions in Power BI.
Exam blueprint weights: Prepare the Data (15-20%), Model the Data (30-35%), Visualize and Analyze (25-30%), Deploy and Maintain (20-25%). Data modeling and DAX carry the most marks — spend the bulk of your study time there.
Domain 1 Sample: Prepare the Data
The Prepare the Data domain tests your ability to get data into Power BI using connectors and Power Query. Expect questions on M language basics, query folding, and dataflows.
You import a CSV file into Power BI. The "Quantity" column has 14 error values caused by text in a numeric column. You need to keep the rows but replace the errors with 0. Which Power Query transformation should you apply?
A. Remove Errors
B. Replace Errors
C. Replace Values
D. Change Type with Errors
Answer: B. Replace Errors. "Replace Errors" lets you substitute a fixed value (like 0) for any error cells while preserving the row. "Remove Errors" deletes the entire row, "Replace Values" cannot target error cells, and "Change Type with Errors" only changes the data type.
Your team has 12 reports that all import the same Customer table from on-premises SQL Server. You want to centralize the data preparation logic so every report uses the same cleaned table. Which feature should you use?
A. Shared dataset
B. Dataflow
C. Power BI Datamart
D. Composite model
Answer: B. Dataflow. Dataflows store reusable Power Query logic and the resulting data in Azure Data Lake Storage Gen2, which any Power BI dataset can reference. Shared datasets reuse a model, not the prep logic. Datamarts add a SQL endpoint — useful but heavier than needed for this scenario.
You connect to an Azure SQL Database. To maximize performance, you want as many transformations as possible to be sent back to the database server. What is this technique called and how do you confirm it?
A. Direct Query / "View Native Query" is enabled
B. Query Folding / right-click the step and check "View Native Query"
C. Push-down / use Performance Analyzer
D. Aggregations / use the DAX Studio
Answer: B. "Query folding" is the term for translating Power Query steps into the source's native query language (T-SQL here). Right-click any step in the Applied Steps pane and choose "View Native Query" — if it is greyed out, that step broke folding.
Domain 2 Sample: Model the Data
The largest domain (30-35%). Tests DAX, relationships, calculation groups, time intelligence, and model design.
You have a Sales fact table linked to a Date dimension. You need a measure showing year-over-year sales growth as a percentage. Which DAX expression is correct?
A. DIVIDE([Sales] - CALCULATE([Sales], DATEADD('Date'[Date], -1, YEAR)), [Sales])
B. DIVIDE([Sales] - CALCULATE([Sales], SAMEPERIODLASTYEAR('Date'[Date])), CALCULATE([Sales], SAMEPERIODLASTYEAR('Date'[Date])))
C. [Sales] / CALCULATE([Sales], PREVIOUSYEAR('Date'[Date]))
D. SUMX('Sales', [Sales] - DATEADD('Date'[Date], -1, YEAR))
Answer: B. YoY growth = (current - previous) / previous. Option A divides by current, giving the wrong denominator. Option C does not subtract first and ignores divide-by-zero. Option D mixes a row-context iterator with a date function in an invalid way.
You're building a model where one Customer can have many Orders, and one Order can have many Order Lines. The Customer table has 100,000 rows, Orders has 500,000, and OrderLines has 4,000,000. What relationship cardinality should you use between Orders and OrderLines, and which direction should the cross-filter flow?
A. One-to-many, single direction (Orders to OrderLines)
B. Many-to-many, both directions
C. One-to-one, single direction
D. One-to-many, both directions
Answer: A. Orders has unique OrderID values, OrderLines has many rows per order, so it's one-to-many with single-direction filtering from the "one" side. Bidirectional filtering on a chain like this creates ambiguous filter paths and slow performance.
Which DAX produces the correct total sales for products with a unit price greater than $50?
A. SUMX(FILTER('Sales', RELATED('Product'[UnitPrice]) > 50), 'Sales'[Amount])
B. CALCULATE(SUM('Sales'[Amount]), 'Product'[UnitPrice] > 50)
C. Both A and B
D. Neither
Answer: C. Both. Both produce identical results when there's an active relationship between Sales and Product. Option B is the more efficient idiom because CALCULATE applies the filter at the storage-engine level. Option A works but iterates row-by-row.
Domain 3 Sample: Visualize and Analyze
This domain covers visuals, drill-through, bookmarks, mobile layout, and AI features (Q&A, anomaly detection, key influencers).
A user clicks a category bar in a chart and lands on a detailed page filtered to that category. Which feature is being used?
A. Drilldown
B. Drillthrough
C. Cross-filter
D. Bookmark
Answer: B. Drillthrough. Drillthrough takes the user to a different report page filtered by the selected value. Drilldown stays on the same visual but moves down a hierarchy. Cross-filter is the chart-to-chart filter on the same page. Bookmarks save state, not navigation.
You want Power BI to automatically highlight unusual spikes and dips in a daily revenue line chart. Which built-in feature should you enable?
A. Forecast
B. Trendline
C. Anomaly detection
D. Decomposition tree
Answer: C. Anomaly detection. Available on line charts in the Analytics pane. It uses an unsupervised SR-CNN algorithm to flag points outside the expected range. Forecast extends the line into the future. Trendline draws a regression line. Decomposition tree breaks down a measure by dimensions.
You need to color the background of a Sales column in a table green when sales exceed target, red when below 80% of target, and yellow otherwise. What conditional formatting rule type should you use?
A. Color scale
B. Rules-based
C. Field value (using a DAX measure)
D. Any of the above
Answer: D. Any of the three approaches works, though "Rules" or "Field value" is cleaner because the thresholds are based on a related metric (target) not a fixed scale. "Field value" with a SWITCH measure scales best when rules grow complex.
Domain 4 Sample: Deploy and Maintain
Tests workspace roles, deployment pipelines, gateways, scheduled refresh, RLS, and sensitivity labels.
Your sales managers should each only see their own region's data. You define a Region role in Power BI Desktop. After publishing, who must add users to the role and where?
A. The report author in Power BI Desktop
B. The dataset owner in the Power BI Service under Security on the dataset
C. The Power BI admin via the admin portal
D. Each user logs in and self-assigns
Answer: B. RLS roles are defined in Desktop but membership is assigned in the Service. Open the dataset in the workspace, choose "Security," then add users or AAD groups to each role. The admin portal does not manage RLS membership.
You publish a report that connects to an on-premises SQL Server. Scheduled refresh fails. What is the most likely cause and fix?
A. The gateway is not installed or the data source is not bound to it
B. The dataset is too large for Pro
C. RLS is misconfigured
D. The Power Query is using DirectQuery
Answer: A. Any on-premises connection requires a configured Standard (Enterprise) Gateway. After installing the gateway, you must add the SQL Server as a data source under "Manage gateways" and bind the dataset to that gateway under "Settings > Gateway connection."
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Start PL-300 PracticeHow to Use Practice Questions Effectively
Practice questions are diagnostic tools, not study tools. Use them to find what you don't know, then go back to the official Microsoft Learn modules or Power BI Desktop to learn the concept hands-on.
- First pass — untimed. Read each question carefully. Try to articulate why each wrong answer is wrong.
- Mark uncertain answers. Even if you got them right by guessing, treat them as wrong and review.
- Re-build the scenario in Power BI Desktop. If a question is about a DAX measure, write it. If it's about a relationship, model it.
- Time-box later attempts. Once you're scoring 75%+ untimed, switch to 100-minute mock exams.
- Re-review wrong answers after 3-5 days. Spaced repetition cements the learning.
Don't memorize answers. Microsoft rotates question banks. If you've seen a question word-for-word from a "brain dump" site, ignore it. Focus on the underlying concept — that's what scales to the actual exam.
PL-300 Pass Strategy
Two weeks before exam
Take a full-length 60-question timed mock. If you score below 65%, push the date back. Identify the lowest-weighted domain by score and dedicate three days to it.
One week before exam
Build a real Power BI report end-to-end: import three tables, model with star schema, write at least five DAX measures including a time-intelligence one, design a two-page report with drillthrough, publish to a workspace, configure RLS, and schedule refresh through a gateway. If you can do this in three hours, you're ready.
Day before
Light review of your weak-area notes. Confirm Pearson VUE or online proctor logistics. Sleep 8 hours.
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Frequently Asked Questions
Are practice questions enough to pass the PL-300?
Practice questions alone are not enough. Microsoft expects you to have hands-on experience with Power BI Desktop and the Power BI Service. Use practice questions to identify weak areas and validate readiness, but spend at least 30-40 hours building real reports in Power BI Desktop. Aim for 80% or higher on full-length practice tests before booking the exam.
How many practice questions should I take before the PL-300?
Plan to complete at least 300-500 unique practice questions before sitting the PL-300. Take three full-length 60-question mock exams under timed conditions in the final week. Repetition matters less than reviewing each wrong answer in detail and understanding the underlying DAX or modeling concept.
When was the PL-300 exam last updated?
Microsoft updates PL-300 objectives roughly every 6-12 months. The most recent significant change moved more weight onto data modeling and DAX while reducing rote Power Query syntax questions. Always check the official PL-300 study guide on the Microsoft Learn site for the current weighted breakdown before scheduling.
What types of questions appear on the PL-300 exam?
The PL-300 mixes single-answer multiple choice, multi-answer multiple choice, drag-and-drop ordering, hot-area pictures, and case-study scenarios. Expect 40-60 total questions across these formats in 100 minutes. The case studies are mini-projects with 5-7 follow-on questions and you cannot revisit them once you advance.
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