PL-300 Timed Practice Test 1 — 10 Questions

Question 1

You are connecting to a data source that contains Personally Identifiable Information (PII). You need to ensure that only authorized users can view the data in Power BI reports. Which TWO actions should you take?

10 minute time limit — choose an answer to begin.

Accepted Answer

Define row-level security (RLS) roles in Power BI Desktop.. Row-Level Security (RLS) allows you to restrict data access at the row level based on user roles defined in Power BI Desktop. By creating roles and using DAX filters, you can ensure that only authorized users see specific rows of PII data when the report is published to the Power BI service and users are mapped to roles.

Answer

Enable encryption at rest for the dataset.

Answer

Use Power Query to mask PII columns by replacing values with '***'.

Answer

Apply sensitivity labels to the dataset.

Question 2

Which TWO of the following are valid ways to share a Power BI report with external users who do not have a Power BI license? (Choose two.)

Accepted Answer

Publish the report to a Power BI app and grant access to external users if the tenant settings allow.. Options A and C are correct. To share a Power BI report with external users without licenses, you can either publish it to a Power BI app (if tenant settings allow external sharing) or use the 'Publish to web' option to generate an embed code that works without requiring a license. Option D (sharing directly) requires the recipient to have a Pro license. Option B (exporting to PDF and emailing) is not a built-in feature. Option E (sharing to a distribution group) still requires licenses for the users.

Answer

Export the report to PDF and email it to the external user.

Answer

Share the report directly from the Power BI service by entering the external user's email address.

Answer

Add the external user to a distribution group and share the report with that group.

Question 3

You are building a Power BI report for a logistics company. The data source is a SQL Server database with tables: 'Shipments' (columns: ShipmentID, OrderDate, ShipDate, CustomerID, Origin, Destination, Weight, Cost, Revenue), 'Customers' (CustomerID, CustomerName, Segment, Country), and 'Calendar' (Date, Year, Month, Quarter). You need to create a star schema in Power BI. You have already created the relationships. When you try to create a measure to calculate the average delivery time (ShipDate - OrderDate), you get an error because the data types are datetime. You want to create a calculated column in the Shipments table that shows the delivery time in days. Which DAX expression should you use?

Accepted Answer

DeliveryDays = DATEDIFF(Shipments[OrderDate], Shipments[ShipDate], DAY). DATEDIFF calculates the difference between two dates in the specified interval (DAY). Option A is incorrect because subtracting datetime values directly may not yield the number of days reliably; it could return a duration object that needs conversion. Option B is incorrect because CALCULATE is not needed for a simple column calculation, and the arguments to DATEDIFF are swapped (OrderDate should be first). Option C is incorrect because FORMAT returns a string, not a numeric value.

Answer

DeliveryDays = Shipments[ShipDate] - Shipments[OrderDate]

Answer

DeliveryDays = CALCULATE(DATEDIFF(Shipments[OrderDate], Shipments[ShipDate], DAY))

Answer

DeliveryDays = FORMAT(Shipments[ShipDate] - Shipments[OrderDate], "d")

Question 4

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 5

You are a Power BI developer for a financial services company. The company has a large transactional database in Azure Synapse Analytics. The database contains a table 'Transactions' with 2 billion rows. The table includes columns: TransactionID, AccountID, TransactionDate, Amount, Type (Deposit/Withdrawal), Status (Pending/Completed). You need to build a Power BI semantic model that allows executives to analyze monthly trends of completed deposit amounts by account type (e.g., Savings, Checking). The account type is in a separate 'Accounts' table (1 million rows) with columns: AccountID, AccountType, CustomerID. The model must refresh within 2 hours. Due to the large data volume, you cannot import the entire Transactions table. What should you do?

Accepted Answer

Create an aggregated table in Synapse that pre-aggregates data at the month and account type level, then use DirectQuery on the aggregated table, and use a composite model with the detail table for drill-through.. Creating an aggregated table in Azure Synapse that pre-aggregates data at the month and account type level drastically reduces the data volume. Using DirectQuery on this aggregated table allows fast querying, and a composite model with the detail table enables drill-through to individual transactions when needed. This approach meets the refresh time constraint and handles large data efficiently. Option A is incorrect because incremental refresh with DirectQuery for older data does not solve the initial load issue and can be complex. Option B is incorrect because Power BI aggregations still require the base data to be imported, which is not feasible with 2 billion rows. Option C is incorrect because DirectQuery on the full table would be too slow for analysis.

Answer

Use incremental refresh to import only recent data, and use DirectQuery for older data.

Answer

Import only the necessary columns and use Power BI aggregations to pre-aggregate.

Answer

Use DirectQuery on the full Transactions table and rely on the Synapse query optimizer.

Question 6

Which TWO DAX functions can be used to filter data in a measure?

Accepted Answer

FILTER. (FILTER) is correct because it is a DAX function specifically designed to return a filtered subset of a table based on a logical condition, making it a primary tool for row-level filtering within measures. Option E (CALCULATE) is correct because it modifies the filter context of a measure by applying or removing filters, effectively filtering data through its filter arguments. Both functions directly control which rows are included in calculations.

Answer

VALUES

Answer

SUM

Answer

ALL

Question 7

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').. 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 8

You are reviewing a Power Query that imports data from SQL Server. The exhibit shows the M code. The SQL query filters records after a date, then Power Query filters rows with OrderQty > 10, and then groups by ProductID. What is a potential performance issue with this approach?

Accepted Answer

The filter on OrderQty > 10 should be included in the SQL query to reduce the amount of data transferred.. Pushing the `OrderQty > 10` filter into the SQL query reduces the amount of data transferred from SQL Server to Power Query. In Power Query, data is loaded into memory before transformations; filtering earlier in the source query minimizes memory usage and network latency, which is a key performance optimization in Power BI data loading.

Answer

The query will fail because the SQL query uses '>' with a string.

Answer

The SQL query should use a parameter for the date instead of a hardcoded value.

Answer

The grouping should be done in SQL to reduce data volume.

Question 9

Which TWO are best practices for optimizing Power Query performance? (Choose two.)

Accepted Answer

Disable the 'Enable background refresh' option in the query settings.. Disabling 'Enable background refresh' prevents Power Query from running queries in the background while you continue working in Power BI Desktop. This ensures that query execution is synchronous, which can improve performance by avoiding resource contention and allowing you to monitor progress directly. Background refresh can cause delays and unexpected behavior when multiple queries run simultaneously, especially with large data sources.

Answer

Merge tables as early as possible in the query to combine data.

Answer

Keep all columns in the table to avoid missing data.

Answer

Split columns by delimiter to normalize data.

Question 10

You have a Power BI report that uses a date table connected to a fact table. You need to ensure that all dates in the fact table are covered by the date table. Which relationship property should you configure?

Accepted Answer

Assume referential integrity. The 'Assume referential integrity' property, when enabled, tells Power BI that every value in the foreign key column of the fact table exists in the primary key column of the date table. This ensures that all dates in the fact table are covered by the date table, allowing Power BI to use more efficient storage and query execution (e.g., INNER JOIN semantics) rather than a full OUTER JOIN.

Answer

Make this relationship active

Answer

Cardinality

Answer

Cross filter direction