PL-300 Practice Test 18 — 15 Questions

Question 1

You are modeling data for a retail company. The fact table contains sales transactions with columns: OrderDate, ProductID, CustomerID, Quantity, and SalesAmount. You also have dimension tables: Date, Product, Customer. The Date table has a relationship to the fact table on OrderDate, and the Customer table has a relationship to the fact table on CustomerID. However, you need to support analysis by both OrderDate and ShipDate. What is the recommended approach?

Accepted Answer

Create a second Date table and add an inactive relationship from ShipDate to the new Date table, then use USERELATIONSHIP in measures. Option D is correct because creating a second Date table with an inactive relationship for ShipDate allows you to use USERELATIONSHIP in measures to switch between active and inactive relationships as needed. Option A is wrong because multiple active relationships cause ambiguity and errors. Option B is wrong because merging ShipDate into a single column loses the original ship date information. Option C is wrong because using the ShipDate directly without a date table limits time intelligence.

Answer

Create a calculated column that combines OrderDate and ShipDate into a single date column

Answer

Add ShipDate as a column in the fact table and use it directly in calculations

Answer

Create two active relationships from the fact table to the Date table: one on OrderDate and one on ShipDate

Question 2

Which TWO are valid reasons to use a star schema design in Power BI? (Select exactly 2.)

Accepted Answer

It improves query performance by reducing the number of joins needed. Options B and D are correct. Option B: Star schema simplifies the model and improves query performance because of fewer joins and a clear structure. Option D: Star schema reduces model size by normalizing dimensions and avoiding duplication. Option A is wrong because star schema does not inherently reduce the number of tables; it typically increases them compared to a flat table. Option C is wrong because star schema supports many-to-one relationships, not many-to-many directly. Option E is wrong because star schema is not specifically required for time intelligence; a date table is needed, but star schema is broader.

Answer

It allows many-to-many relationships between dimensions

Answer

It is required to use time intelligence functions

Answer

It reduces the number of tables in the model

Question 3

You are examining a Power BI model definition. The Date table is generated via Power Query M code. The partition mode is 'import'. What will happen when the dataset refreshes after December 31, 2025?

Accepted Answer

The table will be refreshed with the same date range (2020-2025).. Option C is correct. Since the partition mode is 'import' (not incremental), the entire table is replaced on each refresh. The M code generates dates from 2020-01-01 to 2025-12-31, so after 2025, no new dates will be added unless the code is updated. Option A is wrong because incremental refresh is not configured. Option B is wrong because the table is fully reloaded, not appended. Option D is wrong because the refresh will succeed, but no new dates beyond 2025 will appear.

Answer

The existing table will be appended with new rows.

Answer

The refresh will fail because EndDate is in the past.

Answer

New dates after 2025-12-31 will be added incrementally.

Question 4

Refer to the exhibit. You are managing a Power BI workspace and applying dataset permissions via the XMLA endpoint. The JSON policy shows permissions for two users on the 'Sales' dataset. user1 has Viewer role, user2 has Reshare role. The dataset has row-level security (RLS) defined. Which statement is true about the permissions?

Accepted Answer

Both users will have RLS applied when querying the dataset.. Option A is correct because RLS is enforced for both Viewer and Reshare roles. Option B is incorrect because Reshare allows sharing but not necessarily modifying reports. Option C is incorrect because Viewer cannot modify the dataset. Option D is incorrect because Reshare does not allow editing the dataset.

Answer

user2 can share the dataset with others but cannot build reports.

Answer

user2 can add new measures to the dataset using the XMLA endpoint.

Answer

user1 can modify the dataset structure through the XMLA endpoint.

Question 5

You are reviewing a Power BI model definition in JSON. The Sales table contains a ProductID column but the Product table does not have a ProductID column; instead it has a ProductID column with dataType string. What issue will occur when you try to create a relationship?

Accepted Answer

The relationship will fail because the data types are incompatible. Option C is correct because the data types do not match: Sales.ProductID is int64, while Product.ProductID is string. Power BI relationships require matching data types. Option A is wrong because the column names match, so no rename is needed. Option B is wrong because many-to-one is allowed, but the data type mismatch is the problem. Option D is wrong because the relationship direction is not the primary issue.

Answer

The relationship will fail because the column names must be different

Answer

The relationship will create a cross filter direction of single

Answer

The relationship will work but be many-to-many due to different data types

Question 6

You have a DAX measure that sums the Amount column for rows where Quantity is greater than 10. The Sales table has 10 million rows. What is a potential performance issue with this measure?

Accepted Answer

The SUMX iterator can be slow on large tables; consider using CALCULATE instead. Option D is correct because SUMX iterates over each row in the filtered table, which can be slow for large tables. It is generally more efficient to use CALCULATE with a filter argument. Option A is wrong because the FILTER function does not inherently cause table scans; it creates a filtered table. Option B is wrong because the measure uses a simple condition, not complex. Option C is wrong because the measure is not context-based in a way that would cause issues.

Answer

The FILTER function will cause a full table scan each time the measure is evaluated

Answer

The measure uses context transition which can cause performance issues

Answer

The measure uses a complex condition that cannot be optimized

Question 7

You need to create a hierarchy in Power BI that allows users to drill down from Year to Quarter to Month. Which of the following actions is required?

Accepted Answer

In the Fields pane, right-click a column and select 'Create hierarchy', then add child columns.. Option C is correct. A hierarchy is created by selecting multiple columns in the same table and defining a parent-child relationship. Option A is incorrect because relationships are between tables, not within a hierarchy. Option B is incorrect because hierarchies can be created in the model view, not only in report view. Option D is incorrect because you cannot create a hierarchy in Power Query.

Answer

Create a relationship between the Year, Quarter, and Month columns.

Answer

Create the hierarchy in the report view by grouping fields.

Answer

Use Power Query to merge the columns into one.

Question 8

Refer to the exhibit. You are using DAX Studio to profile a Power BI semantic model. The query above returns a table with sales totals by year and product category. However, you notice that the results do not include rows for years or categories with no sales. Which DAX function should you use to ensure all combinations of year and category appear, even with blank sales?

Accepted Answer

CROSSJOIN. Option D is correct because CROSSJOIN generates all combinations of the columns, then you can left join with the sales table. Option A is for cross-tabulation. Option B is an older function that may not handle blanks well. Option C is not a valid DAX function.

Answer

ADDCOLUMNS

Answer

SUMMARIZE

Answer

EXPAND

Question 9

Which THREE of the following are considerations when implementing row-level security (RLS) in Power BI? (Select three.)

Accepted Answer

RLS does not apply to data accessed via the XMLA endpoint unless using dynamic security.. Options A, C, and E are correct. RLS is applied when the user queries the dataset (A). It can be defined using DAX filters (C). It does not apply to the XMLA endpoint by default unless dynamic (E). Option B is incorrect because RLS filters apply to all visuals. Option D is incorrect because RLS is user-based, not role-based in terms of dynamic security.

Answer

RLS is enforced only for users with the Viewer role.

Answer

RLS can be bypassed by using the 'Show all' option in visuals.

Question 10

You have a Power BI model with a table 'Sales' that contains a column 'OrderDate'. You need to create a calculated column that extracts the year from OrderDate. Which DAX expression should you use?

Accepted Answer

YEAR(Sales[OrderDate]). Option B is correct because YEAR function returns the year from a date. Option A is wrong because FORMAT returns text. Option C is wrong because DATEPART is not a DAX function (it is SQL). Option D is wrong because CALENDAR returns a table, not a scalar.

Answer

DATEPART("year", Sales[OrderDate])

Answer

CALENDAR(YEAR(Sales[OrderDate]), YEAR(Sales[OrderDate]))

Answer

FORMAT(Sales[OrderDate], "yyyy")

Question 11

When creating a many-to-many relationship between two tables, what is a common approach to model this in Power BI?

Accepted Answer

Introduce a bridge table that contains the unique combinations.. Option B is correct because a bridge table resolves many-to-many relationships by creating two one-to-many relationships. Option A is wrong because a single many-to-many relationship without a bridge table is not supported directly. Option C is wrong because CROSSJOIN creates a Cartesian product, which is not correct. Option D is wrong because merging tables into one removes the relationship structure.

Answer

Use the CROSSJOIN DAX function in calculated tables.

Answer

Merge both tables into a single table.

Answer

Create a direct many-to-many relationship in the model.

Question 12

You have a Power BI model with tables: Sales (DateKey, Amount) and Date (DateKey, Year, Month, Day). The measure above is intended to show sales for the current year ignoring any filters on date. However, when placed in a matrix with Month on rows, it returns the same value for every month. What is the most likely reason?

Accepted Answer

The FILTER function removes month context from the Date table. The FILTER function uses ALL(Date) which removes all filters from the Date table, including the month filter from the matrix row context. Therefore, the measure always returns the total sales for the entire current year regardless of the month. Option B is correct. Option A is wrong because the expression is valid syntactically. Option C is wrong because there is no relationship ambiguity issue. Option D is wrong because the table name is used correctly.

Answer

The CALCULATE function is misused and should be replaced with SUMX

Answer

The Date table is not marked as a date table

Answer

The relationship between Sales and Date is inactive

Question 13

You are reviewing a Power BI model definition with incremental refresh policy. The Sales table has an incremental refresh policy that refreshes the last 365 days. However, the report shows data for dates beyond 365 days ago. What is the most likely reason?

Accepted Answer

Incremental refresh only refreshes the data, it does not remove historical data. Option B is correct because incremental refresh policy only affects refresh operations; it does not delete historical data from the model. Data older than 365 days remains in the model unless explicitly removed. Option A is wrong because the policy is defined for the table, not partitions. Option C is wrong because the policy is set to refresh the last 365 days, not filter. Option D is wrong because incremental refresh does not automatically remove old data; it only refreshes recent data.

Answer

The incremental refresh policy is applied at the partition level instead of the table level

Answer

The incrementalPeriodsOffset should be set to a negative value to include historical data

Answer

The refresh policy automatically removes data older than the incremental period

Question 14

You are reviewing a Power BI model definition in TMSL. The model has incremental refresh configured with two partitions. When the model refreshes on July 1, 2024, which data will be refreshed in Partition1?

Accepted Answer

All rows where OrderDate is between 2024-01-01 and 2024-04-01.. Option C is correct. Incremental refresh partitions use parameters like RangeStart and RangeEnd. In this example, the partitions are hardcoded dates. On July 1, 2024, Partition1 covers data from Jan 1 to Apr 1, which is in the past, so it will be fully refreshed. Option A is wrong because only past data is refreshed. Option B is wrong because incremental refresh refreshes all data in the partition, not just changes. Option D is wrong because the partition is not excluded.

Answer

Only new rows added since last refresh.

Answer

No data, because the partition is in the past.

Answer

Only data modified since the last refresh.

Question 15

You have a Power BI model with a table 'Sales' and a separate 'Calendar' table. The relationship between Sales[OrderDate] and Calendar[Date] is active. You need to create a measure that calculates the total sales for the previous month relative to the current filter context. Which DAX expression should you use?

Accepted Answer

CALCULATE(SUM(Sales[Amount]), DATEADD(Calendar[Date], -1, MONTH)). Option C is correct. CALCULATE with DATEADD shifting by -1 month returns the same period last month. Option A uses PREVIOUSMONTH which is equivalent but requires a continuous date range; DATEADD is more flexible. Option B returns dates in the next month. Option D returns dates in the same month of previous year.

Answer

CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR(Calendar[Date]))

Answer

CALCULATE(SUM(Sales[Amount]), NEXTMONTH(Calendar[Date]))

Answer

CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Calendar[Date]))