PL-300 Practice Test 47 — 15 Questions

Question 1

You are a Power BI administrator. A user reports that they cannot see any data when they open a report that uses row-level security (RLS). The user is a member of the 'Sales' RLS role, which filters data to [Region] = 'North America'. However, the report shows blank visuals. What is the most likely cause?

Accepted Answer

The RLS filter uses an exact string match, but the actual region values in the data are different (e.g., 'North America' vs 'North America ' or 'NA').. Option D is correct because if the 'North America' region name in the data does not exactly match the filter (e.g., 'North America' vs 'NA'), the filter will not match any rows. Option A is wrong because the user can see the report, just no data. Option B is wrong because RLS roles are usually defined in Desktop. Option C is wrong because the user is in the Sales role, so they should see data.

Answer

The user does not have permission to view the report.

Answer

The user is also a member of a workspace role that overrides RLS.

Answer

The RLS role was defined in the Power BI service after publishing, but the user was not added.

Question 2

You manage a Power BI environment where users frequently share reports by sending the URL from the browser. However, external recipients often receive an error saying they cannot access the report. What is the most likely reason?

Accepted Answer

The 'Share content with external users' setting is disabled in the tenant.. Option D is correct. By default, sharing with external users requires the 'Share with external users' setting to be enabled in the Power BI admin portal. Option A is wrong because external users do not need a Power BI Pro license if the report is shared to them; they can view it if the setting is enabled. Option B is wrong because external users can access the report even if they are not in the same tenant. Option C is wrong because the report is already published to the service.

Answer

External users do not have a Power BI Pro license.

Answer

External users are not part of the same Microsoft Entra tenant.

Answer

The report is not published to the Power BI service.

Question 3

A Power BI developer has a fact table that contains sales data at the transaction level. The table includes columns: TransactionID, ProductID, CustomerID, DateKey, Quantity, UnitPrice, Discount, and SalesAmount. The developer wants to create a measure for total sales after discount. Which approach is best for performance and accuracy?

Accepted Answer

Add a calculated column in Power Query: NetAmount = Quantity * UnitPrice - Discount, then create a measure: SUM(Sales[NetAmount]). Option B is correct because it performs the net amount calculation at the row level in Power Query (M), which is computed during data refresh and stored in the table. This avoids runtime row-by-row iteration in DAX, making the measure SUM(Sales[NetAmount]) a simple, highly efficient aggregation. It ensures both performance and accuracy, as the discount is applied per transaction before aggregation.

Answer

Create a measure: SUM(Sales[SalesAmount]) - SUM(Sales[Discount])

Answer

Create a measure: SUMX(Sales, Sales[Quantity] * Sales[UnitPrice] - Sales[Discount])

Answer

Create a measure: SUM(Sales[Quantity] * Sales[UnitPrice]) - SUM(Sales[Discount])

Question 4

A data model has a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. There is a 'Customers' table with columns: CustomerID, CustomerName. To analyze orders by customer, what is the best practice for modeling the relationship?

Accepted Answer

Create a one-to-many relationship from Customers to Orders with single direction.. Option A is correct because in a star schema, the Customers table (dimension) should have a one-to-many relationship to the Orders table (fact) filtered from the dimension side. This single-direction filter propagation ensures that when a customer is selected, only their orders are shown, while preventing unwanted cross-filtering from orders back to customers. This is the standard best practice for modeling dimension-to-fact relationships in Power BI.

Answer

Create a one-to-one relationship between Customers and Orders based on CustomerID.

Answer

Create an inactive relationship and use USERELATIONSHIP in measures.

Answer

Create a many-to-one relationship from Orders to Customers with both directions.

Question 5

A company has a fact table 'Sales' with a column 'SalesAmount' and a dimension table 'Date'. They want to create a measure that calculates the running total of sales over time. The Date table is marked as a date table. Which DAX expression is correct?

Accepted Answer

Running Total = CALCULATE(SUM(Sales[SalesAmount]), DATESYTD(Date[Date])). Option B is correct because DATESYTD returns a set of dates from the start of the year to the latest date in the current filter context, and when wrapped in CALCULATE, it correctly computes a year-to-date running total. Since the Date table is marked as a date table, DATESYTD works seamlessly with the time intelligence functions in DAX.

Answer

Running Total = CALCULATE(SUM(Sales[SalesAmount]), FILTER(ALL(Date), Date[Date] <= EARLIER(Date[Date])))

Answer

Running Total = TOTALYTD(SUM(Sales[SalesAmount]), Date[Date])

Answer

Running Total = SUMX(Sales, Sales[SalesAmount])

Question 6

Which THREE of the following are valid reasons to create a calculated table in Power BI?

Accepted Answer

To create a date table that is not available in the data source.. Option C is correct because calculated tables in Power BI are created using DAX and stored in memory, allowing you to generate a date table when no suitable date table exists in the data source. This is a common pattern to ensure a complete date range for time intelligence functions, as Power BI requires a continuous date table for functions like TOTALYTD or SAMEPERIODLASTYEAR.

Answer

To add a column that computes a value based on other columns in the same table.

Answer

To combine two tables by merging columns from one table into another.

Question 7

A company has a large fact table with sales data. The Sales table contains columns: OrderDate, ShipDate, DueDate, LineTotal, ProductKey, CustomerKey, TerritoryKey. The company needs to analyze sales by fiscal year (April 1 to March 31) and by calendar year. What is the recommended approach to model the date dimension?

Accepted Answer

Use a single date dimension table and keep only one active relationship (e.g., to OrderDate). For other dates, create measures that filter the date table using CALCULATE and FILTER.. Option A is correct because it uses a single date dimension table with one active relationship (typically to OrderDate) and leverages CALCULATE with FILTER or USERELATIONSHIP for other date roles. This is the recommended star schema design in Power BI, as it avoids unnecessary table duplication and maintains model simplicity while supporting fiscal year analysis via a calculated column in the date table.

Answer

Create a separate date dimension table for each date column in the Sales table and relate each to the fact table.

Answer

Use a single date dimension table and create multiple active relationships using bridging tables or by duplicating the dimension table for each role.

Answer

Use a single date dimension table and create inactive relationships for ShipDate and DueDate. Use USERELATIONSHIP in DAX measures.

Question 8

A company has a Power BI semantic model that uses Import mode. The model contains a table with 10 million rows. The data source is a SQL Server view that takes 5 minutes to execute. The scheduled refresh is set to every hour. What is the likely impact on refresh performance?

Accepted Answer

Refresh will take at least 5 minutes plus data loading time.. Option D is correct because the refresh process must first execute the SQL Server view to retrieve data, which takes at least 5 minutes, and then load that data into the Import mode model. The total refresh time is the sum of the query execution time and the data loading time, so it will be at least 5 minutes plus additional time for loading 10 million rows.

Answer

Refresh will fail due to timeout on the gateway.

Answer

The model will automatically use incremental refresh to split the load.

Answer

Refresh will complete in parallel with the view execution.

Question 9

After loading the data using the Power Query M code shown in the exhibit, the model contains a table with 10,000 rows. However, when users filter by OrderDate in a report, the filter does not affect the aggregated TotalDue values. What is the most likely reason?

Accepted Answer

The data is pre-aggregated in Power Query, so report-level filters cannot re-aggregate.. Option C is correct because the GROUP BY and aggregation happen in Power Query before loading, so the data is pre-aggregated and static. Filters applied in the report cannot re-aggregate because the underlying detail is lost. Option A is wrong because the Date table relationship is not the issue; the data is already aggregated. Option B is wrong because the data type is fine. Option D is wrong because the refresh is not related.

Answer

The TotalDue column is not a numeric type.

Answer

The dataset is not refreshing properly.

Answer

The Date table has no relationship to the Sales table.

Question 10

A company has a fact table with sales data and multiple dimension tables. They want to create a measure that calculates the total sales amount for the current year, but the measure returns incorrect results when used in a visual with a date hierarchy. What is the most likely cause?

Accepted Answer

The relationship between the date table and the fact table is inactive.. Option C is correct because if the relationship between the date table and the fact table is inactive, measures that rely on time intelligence functions (like TOTALYTD, SAMEPERIODLASTYEAR, or a simple SUM with date filtering) will not automatically propagate filters from the date hierarchy to the fact table. In Power BI, only one active relationship can exist between two tables; inactive relationships require explicit activation via USERELATIONSHIP in DAX. Without that, the measure ignores the date filter and returns incorrect or blank results.

Answer

The date table is not marked as a date table in Power BI.

Answer

The fact table is not in a star schema; it is snowflaked.

Answer

The relationship between the date table and the fact table is set to bidirectional cross-filtering.

Question 11

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model contains a large fact table with sales data. Users report that reports using this model are slow. Which design change would most improve query performance?

Accepted Answer

Remove unnecessary columns from the fact table.. Option C is correct because removing unnecessary columns from the fact table reduces the amount of data that must be transferred from SQL Server to Power BI for each query. In DirectQuery mode, every report interaction sends a query to the source database, so fewer columns mean smaller result sets and faster query execution. This directly addresses the performance bottleneck caused by a large fact table without changing the underlying storage mode.

Answer

Remove all relationships between tables.

Answer

Switch the model to Import mode.

Answer

Disable the 'Reduce queries' option in report settings.

Question 12

A data model contains a table 'Sales' with columns: Date, ProductID, Quantity, Amount. There is a 'Products' table with columns: ProductID, ProductName, CategoryID. A measure 'Total Sales' = SUM(Sales[Amount]) returns correct values. However, when a user creates a visual with CategoryID from 'Products' and 'Total Sales', some categories show blank. What is the most likely cause?

Accepted Answer

There are ProductID values in Sales that do not exist in Products table.. Option A is correct because when ProductID values in the Sales table do not have matching entries in the Products table, the relationship between the two tables will result in blank CategoryID values for those unmatched rows. In Power BI, a many-to-one relationship (the default) filters from the 'one' side (Products) to the 'many' side (Sales), but if a Sales row has a ProductID not present in Products, it cannot be matched, and any column from Products (like CategoryID) will appear as blank in visuals. This is a classic data integrity issue where the fact table contains orphaned foreign keys.

Answer

The 'Total Sales' measure is not properly referencing the Sales table.

Answer

The relationship between Sales and Products is set to many-to-one, single direction.

Answer

The relationship is set to both directions (bidirectional).

Question 13

A Power BI report uses a DirectQuery data source. The model includes a calculated column that uses the RELATED function to bring a value from another table. The report is performing slowly. What design change would most improve performance without compromising functionality?

Accepted Answer

Replace the calculated column with a calculated table that includes the related column.. Option D is correct because replacing the calculated column with a calculated table that includes the related column moves the join logic to query time, reducing the per-row overhead of the RELATED function in DirectQuery mode. In DirectQuery, calculated columns are evaluated row-by-row for each query, which can cause significant performance degradation; a calculated table is materialized once during refresh (or in DirectQuery, it is resolved as a single query to the source), avoiding repeated row-level lookups. This change preserves the functionality of having the related value available in the table while improving query performance.

Answer

Remove the RELATED function and merge tables in the source query.

Answer

Convert the model to Import mode.

Answer

Use a measure instead of a calculated column.

Question 14

What is the most likely cause of the error in the DAX query shown in the exhibit?

Accepted Answer

The [Sales Amount] measure is returning multiple values or is not a valid scalar measure.. The error 'A single value for column 'Sales Amount' in table 'Sales' cannot be determined' occurs because the [Sales Amount] measure is being used in a context that expects a scalar value, but the measure is defined to return multiple values (e.g., using SUMX over a table that returns multiple rows without proper aggregation). In DAX, measures used in EVALUATE statements must return a single scalar value; if the measure is not properly aggregated or contains a many-to-many relationship, it can produce multiple values, causing this error.

Answer

There is no relationship between Date and Product tables.

Answer

The SUMMARIZECOLUMNS function does not support multiple group-by columns.

Answer

The ORDER BY clause is not allowed in EVALUATE statements.

Question 15

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?

Accepted Answer

Calculated tables are static and do not respond to slicer selections.. 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.

Answer

The calculated table lacks a relationship to the Sales table.

Answer

The SUMMARIZE function syntax is incorrect.

Answer

The calculated table is not marked as a date table.