PL-300 Practice Test 20 — 15 Questions

Question 1

You are designing a data model for a sales analysis report. The source data includes a table named 'Sales' with columns: OrderDate, CustomerID, ProductID, Quantity, and SalesAmount. You need to create a date table to support time intelligence calculations. Which approach should you use?

Accepted Answer

Create a date table using CALENDAR function with a continuous date range covering all possible dates, then use Mark as Date Table in the model view. Option C is correct because creating a separate date table with a continuous date range and marking it as a date table using the Mark as Date Table feature allows DAX time intelligence functions like TOTALYTD and SAMEPERIODLASTYEAR to work correctly. Option A is wrong because generating dates from the earliest to latest order dates may miss dates with no sales, causing gaps. Option B is wrong because using only distinct order dates from Sales table does not create a continuous date range. Option D is wrong because using DAX CALENDARAUTO without marking as date table may not be recognized by time intelligence functions.

Answer

Use the CALENDARAUTO function to automatically generate dates and rely on auto date/time

Answer

Use the DISTINCT function on Sales[OrderDate] to create a date table

Answer

Create a date table using CALENDAR function with start date = MIN(Sales[OrderDate]) and end date = MAX(Sales[OrderDate])

Question 2

Which THREE of the following are best practices for designing a Power BI data model?

Accepted Answer

Implement business logic in measures rather than calculated columns. Options A, C, and E are correct. A star schema is recommended. Relationships should be based on surrogate keys. Business logic should be in measures. Option B is wrong because composite keys are not recommended; use surrogate keys. Option D is wrong because bidirectional filtering is used sparingly, not by default.

Answer

Use composite keys in relationships for better performance

Answer

Enable bidirectional cross-filtering by default

Question 3

Which THREE considerations are important when designing a date table for time intelligence?

Accepted Answer

The date table must be marked as a date table in Power BI.. Option A is correct because a continuous date range is required. Option B is correct because marking as a date table is required for time intelligence. Option D is correct because a date table should have a relationship to the fact table. Option C is wrong because calculated columns are not a requirement. Option E is wrong because multiple date tables are not a requirement.

Answer

All date columns must be calculated columns.

Answer

The model must have exactly one date table.

Question 4

You have a Power BI model where the Sales table is filtered by a Customer dimension. Users report that when they filter a measure from the Customer table (e.g., Customer Count), it does not affect the Sales visual. What is the most likely cause?

Accepted Answer

The cross-filtering direction is set to one direction (Customer -> Sales), but the filter is applied on Customer. The crossFilteringBehavior is set to 'oneDirection', which means filters flow only from Customer to Sales, not the other way. To allow Customer filters to affect Sales, it should be 'bothDirections' or use bidirectional cross-filtering. Option A is correct. Option B is wrong because security filtering does not impact user filtering. Option C is wrong because the relationship is active. Option D is wrong because the cardinality is not specified but oneDirection is the key.

Answer

The relationship is inactive

Answer

The relationship cardinality is many-to-many

Answer

The security filtering behavior is set to oneDirection

Question 5

You are modeling data from multiple sales regions. Each region has a unique ID, but region names might be spelled inconsistently (e.g., 'North America' vs. 'N. America'). You need to create a single dimension table for regions. What is the best practice to handle this?

Accepted Answer

Use Power Query to clean and standardize region names before loading. Option C is correct: Standardize region names using Power Query transformations before loading into the model. Option A is wrong because keeping inconsistent spellings causes incorrect grouping. Option B is wrong because many-to-many relationships should be avoided if possible. Option D is wrong because hiding columns doesn't fix data quality.

Answer

Keep both spellings in the dimension and use a many-to-many relationship

Answer

Hide the region column and use only region ID in visuals

Answer

Use a bridge table to map both spellings to a single region ID

Question 6

Which TWO actions should you take to improve the performance of a DirectQuery model in Power BI? (Select two.)

Accepted Answer

Limit the columns selected to only those needed in the report.. Options A and D are correct. Reducing the number of columns queried and applying filters early minimize data transfer. Option B is wrong because calculated columns in DirectQuery are pushed to the source and can degrade performance. Option C is wrong because increasing row-level security complexity adds overhead. Option E is wrong because aggregations are not supported in DirectQuery mode.

Answer

Use calculated columns instead of measures to precompute values.

Answer

Create aggregations on the imported tables.

Answer

Implement row-level security filters on the fact table.

Question 7

You are modeling a many-to-many relationship between 'Students' and 'Courses' via a junction table 'Enrollments'. You need to create a measure that counts the number of students enrolled in at least one course. The relationship between Students and Enrollments is one-to-many, and between Courses and Enrollments is one-to-many. What DAX measure should you use?

Accepted Answer

DISTINCTCOUNT(Students[StudentID]). Option B is correct. DISTINCTCOUNT on Students[StudentID] counts unique students, which works correctly with many-to-many because the filter from Courses propagates to Enrollments and then to Students. Option A counts rows in Enrollments, which could be multiple per student. Option C counts courses, not students. Option D counts students but only those with enrollments; however, the filter context may cause blanks. DISTINCTCOUNT is safer.

Answer

COUNTROWS(Enrollments)

Answer

COUNT(Courses[CourseID])

Answer

COUNTA(Students[StudentID])

Question 8

You are modeling a fact table that contains sales transactions with columns: OrderDate, ShipDate, SalesAmount, CustomerKey. You need to create a relationship to a date table. The date table has a single Date column. Which relationship should you create for the most accurate time-based analysis?

Accepted Answer

Create an active relationship from OrderDate to Date and an inactive relationship from ShipDate to Date.. Option C is correct because you should create an active relationship from OrderDate to Date for standard reporting, and an inactive relationship from ShipDate to Date that can be activated using USERELATIONSHIP. Option A would have multiple active relationships causing ambiguity. Option B is not recommended as it omits an important date. Option D is incorrect because you can have multiple relationships, one active and others inactive.

Answer

Create a single relationship from OrderDate to Date and ignore ShipDate.

Answer

Create two active relationships: OrderDate to Date and ShipDate to Date.

Answer

Create only one relationship from ShipDate to Date.

Question 9

Which THREE of the following are valid ways to model a many-to-many relationship between tables in Power BI? (Select three.)

Accepted Answer

Create two one-to-many relationships and use USERELATIONSHIP in measures.. Options A, B, and D are valid techniques. Using a bridge table (A) is common. Using CROSSFILTER with Many-to-Many cardinality (B) is a built-in feature. Using the USERELATIONSHIP function (D) can handle multiple relationships. Option C is incorrect because calculated columns do not create relationships. Option E is incorrect because lookup functions are for one-to-many.

Answer

Use the LOOKUPVALUE function in a measure.

Answer

Add a calculated column to one table to create a unique key.

Question 10

You are designing a data model for a financial analysis report. The source data includes a 'Budget' table with columns: Department, Account, Month, and BudgetAmount. The 'Actuals' table has the same structure. You need to create a combined measure that shows the variance (Actual - Budget) for each Department and Account. What is the best approach?

Accepted Answer

Create separate dimension tables for Department and Account, and create fact tables for Budget and Actuals with relationships. Option B is correct because using a star schema with separate dimension tables for Department and Account and a fact table with both Actual and Budget amounts (or two fact tables) allows easy comparison. Option A is wrong because merging into one table denormalizes. Option C is wrong because it does not use proper dimensions. Option D is wrong because using only DAX without relationships is not scalable.

Answer

Create a single table by merging Budget and Actuals on Department, Account, and Month

Answer

Create a calculated table using SUMMARIZE and then use DAX measures

Answer

Use Power Query to append Budget and Actuals with a 'Type' column

Question 11

You need to create a calculated column that categorizes products based on price: 'Low' (<$10), 'Medium' ($10-$50), 'High' (>$50). Which DAX expression should you use?

Accepted Answer

SWITCH(TRUE(), Product[Price] < 10, "Low", Product[Price] <= 50, "Medium", "High"). Option A is correct because SWITCH evaluates conditions in order and returns the first match, which is appropriate for this scenario. Option B is wrong because IF cannot handle three categories efficiently. Option C is wrong because the syntax is incorrect (no condition after SWITCH). Option D is wrong because LOOKUPVALUE is for looking up values in another table, not for conditional logic.

Answer

SWITCH(Product[Price], <10, "Low", <=50, "Medium", "High")

Answer

LOOKUPVALUE(Category, Product[Price], Product[Price])

Answer

IF(Product[Price] < 10, "Low", Product[Price] <= 50, "Medium", "High")

Question 12

You are building a star schema in Power BI. Your fact table contains sales data at the transaction level. Which of the following is the best practice for modeling the date dimension to support time intelligence functions like year-to-date (YTD) calculations?

Accepted Answer

Create a date table with a contiguous range of dates and mark it as a date table. In a star schema, a dedicated date dimension table with a contiguous range of dates is essential for proper time intelligence. A single date column in the fact table is not sufficient because it lacks attributes like year, month, and quarter. Option C is correct. Option A is wrong because multiple date columns in the fact table would violate normalization. Option B is wrong because a date table covering only sales dates would miss dates with no sales, causing incorrect YTD totals. Option D is wrong because the date table should have a unique date key.

Answer

Use the fact table's date column directly in measures without a date table

Answer

Create a date table with only the dates that appear in the fact table

Answer

Use multiple date columns (e.g., OrderDate, ShipDate) in the fact table

Question 13

You have a Power BI data model with a table 'Orders' related to 'Customers' (one-to-many). A measure calculates total sales per customer. Some customers have no orders, but they still appear in the report with blank sales. What should you do to hide these customers?

Accepted Answer

Remove customers with no orders from the Customers table using Power Query. Option D is correct because removing them from the Customers table ensures they don't appear. Option A is wrong because filtering the visual would be a workaround, not a model fix. Option B is wrong because changing relationship direction doesn't solve the issue. Option C is wrong because marking as date table is irrelevant.

Answer

Change the relationship cross-filter direction to both

Answer

Add a visual-level filter to exclude blanks

Answer

Mark the date table as a date table

Question 14

Refer to the exhibit. You have defined row-level security (RLS) in a Power BI semantic model using Role-level security. The JSON shows three rules for the 'Sales' and 'Targets' tables. The user 'john@contoso.com' belongs to this role. John's manager column in the Sales table has the value 'john@contoso.com'. What data will John see when he queries the model?

Accepted Answer

Sales rows where Region is 'West' and Manager is 'john@contoso.com'; Targets rows where Region is 'West'.. Option A is correct because RLS rules are combined with AND logic. John will see only Sales rows where Region is 'West' AND Manager is 'john@contoso.com'. For Targets, only rows with Region 'West'. Option B is incorrect because OR is not used. Option C is incorrect because both rules on Sales apply. Option D is incorrect because all rules apply.

Answer

All Sales and Targets data because John is a manager.

Answer

Sales rows where Region is 'West' OR Manager is 'john@contoso.com'; Targets rows where Region is 'West'.

Answer

Only Sales rows where Manager is 'john@contoso.com'; no Targets restriction.

Question 15

You are building a Power BI model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, and TotalAmount. You also have a table 'Customers' with columns: CustomerID, CustomerName, and Segment. You need to create a relationship between Orders and Customers on CustomerID. Which relationship configuration should you choose to ensure that filtering Customers by Segment correctly filters Orders?

Accepted Answer

One-to-many relationship from Customers to Orders. Option B is correct because a one-to-many relationship from Customers (one side) to Orders (many side) with Customers filtering Orders is the standard star schema design. Option A is wrong because many-to-one would reverse the direction. Option C is wrong because many-to-many is unnecessary and can cause ambiguity. Option D is wrong because a one-to-one relationship is not appropriate as one customer can have many orders.

Answer

Many-to-one relationship from Orders to Customers

Answer

Many-to-many relationship with a bridge table

Answer

One-to-one relationship