20+ practice questions focused on Model the data — one of the most tested topics on the Microsoft Power BI Data Analyst PL-300 exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Model the data PracticeA Power BI developer creates a star schema with a fact table Sales and dimension tables Customer, Product, Date. The relationship between Sales and Date is active. The developer wants to create a measure that calculates the total sales for the previous month relative to any selected month. Which DAX expression should the developer use?
Explanation: PREVIOUSMONTH(Date[Date]) returns a set of dates for the full previous month relative to the last date in the current filter context. When wrapped in CALCULATE, it shifts the filter on the Date dimension to the prior month, correctly computing total sales for the previous month regardless of the selected month.
A Power BI data model includes a table 'Orders' with columns OrderID, CustomerID, OrderDate, SalesAmount. The model also has a 'Date' table and a 'Customer' table. The relationships are: Orders[CustomerID] -> Customer[CustomerID] (many-to-one, single direction) and Orders[OrderDate] -> Date[Date] (many-to-one, single direction). A user creates a measure that sums SalesAmount and then filters by a slicer on Customer[City]. The slicer works correctly. However, when the user adds another slicer on Date[Year], the measure does not respect both slicers simultaneously. What is the most likely cause?
Explanation: The measure likely uses ALL or ALLEXCEPT, which removes the filter context from the Date table. Even though the relationships are correctly configured and filters from the Date slicer propagate to Orders via the single-direction relationship, if the measure explicitly ignores those filters using a function like ALL(Date[Year]) or ALLEXCEPT(Orders, ...), the Date slicer will have no effect on the measure. This is a common DAX mistake where filter removal functions override slicer selections.
A Power BI developer is designing a data model for sales analysis. The model includes a Sales fact table and dimension tables: Product, Customer, Date, and Store. Which TWO design considerations are best practices for optimizing query performance?
Explanation: Creating a separate date table and marking it as a date table enables Power BI to use built-in time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) that rely on a continuous, contiguous date range. This design ensures optimal performance by allowing the engine to generate efficient DAX queries and leverage date-based relationships without ambiguity.
A Power BI developer is building a data model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, ShipDate, SalesAmount. The developer wants to analyze orders by both order date and ship date. Which THREE actions should the developer take to properly model this scenario?
Explanation: The USERELATIONSHIP function in DAX allows the developer to temporarily activate an inactive relationship for a specific calculation. In this scenario, one relationship (e.g., between Orders[OrderDate] and a date table) is active, while the other (e.g., between Orders[ShipDate] and the same or another date table) is inactive. By using USERELATIONSHIP in measures, the developer can specify which relationship to use for filtering or aggregation, enabling analysis by both order date and ship date without altering the model's default behavior.
A Power BI developer is troubleshooting a report that uses a calculated table. The calculated table is defined as: 'Sales Summary = SUMMARIZE(Sales, Sales[ProductID], "Total Sales", SUM(Sales[Amount]))'. Users report that the 'Total Sales' column shows incorrect values when slicers are applied to the report. What is the most likely cause?
Explanation: Calculated tables in Power BI are evaluated at data refresh time and stored in the model as static data. They do not respond to slicer selections or any other report-level filters because they are not recalculated in the query context. Therefore, the 'Total Sales' column in the 'Sales Summary' table will always show the same aggregated values regardless of slicer interactions, which is why users see incorrect values when applying slicers.
+15 more Model the data questions available
Practice all Model the data questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Model the data. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Model the data questions on the PL-300 frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Model the data is tested as part of the Microsoft Power BI Data Analyst PL-300 blueprint. Practicing with targeted Model the data questions ensures you can handle any format or difficulty that appears.
Yes. Courseiva provides free PL-300 practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.
Difficulty is subjective, but Model the data is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
Launch a full Model the data practice session with instant scoring and detailed explanations.
Start Model the data Practice →