PL-300 Practice Test 2 — 30 Questions

Question 1

You are creating a Power BI report and need to add a visual that allows users to dynamically change the measure displayed in a chart. Which feature should you use?

Accepted Answer

Field parameters. Field parameters provide a way to let report users choose which measures or dimensions appear in a visual. By adding a field parameter to a slicer, users can select from a list of measures, and the visual updates accordingly. This is the most efficient method to achieve dynamic measure switching without creating multiple visuals or bookmarks.

Answer

Bookmarks

Answer

What-if parameters

Answer

Calculation groups

Question 2

Which TWO actions can improve performance of a Power BI DirectQuery model?

Accepted Answer

Ensure proper indexing in the source database. Proper indexing in the source database reduces the query execution time for DirectQuery models. DirectQuery sends queries to the source database in real-time, so efficient indexes on columns used in filters, joins, and aggregations minimize table scans and improve retrieval speed.

Answer

Switch the model to Import mode

Answer

Enable bidirectional cross-filtering on all relationships

Answer

Use calculated columns with complex logic

Question 3

You are building a Power BI data model from an Azure SQL Database. The source table contains a column 'OrderDate' of type datetime. You want to create a date table in Power Query that includes all dates from the minimum to maximum OrderDate. Which M function should you use to generate the list of dates?

Accepted Answer

List.Dates. `List.Dates` generates a list of sequential dates (type `date`) given a start date, a count of values, and a step duration. In Power Query, when you need a date table covering the range from the minimum to maximum `OrderDate`, you compute the count as `Duration.Days(MaxDate - MinDate) + 1` and use `List.Dates(MinDate, Count, #duration(1,0,0,0))`. This produces a clean list of dates without time components, ideal for a date dimension.

Answer

List.Generate

Answer

List.DateTimes

Answer

List.Range

Question 4

Which THREE of the following are best practices when designing Power BI reports for mobile devices? (Select three.)

Accepted Answer

Create a dedicated mobile layout view. Option A is correct because Power BI Desktop provides a dedicated Mobile Layout view (View > Mobile Layout) that lets you rearrange and resize visuals specifically for phone portrait orientation without affecting the desktop canvas. Option B is correct because small phone screens and varied lighting conditions make large font sizes and high-contrast colors essential for legibility and accessibility on mobile devices. Option D is correct because limiting each page to roughly 3-5 visuals keeps the mobile layout scannable and avoids excessive vertical scrolling and slow rendering on phones. Option C is not a mobile best practice per se: custom visuals are chosen for analytical capability, not for mobile optimization, and some custom visuals render poorly or are not optimized for small screens. Option E is not recommended because stacking multiple slicers consumes scarce screen space and complicates touch interaction; mobile designs typically favor a single, well-chosen slicer or filter pane instead.

Answer

Use custom visuals for advanced analytics

Answer

Include multiple slicers for flexible filtering

Question 5

You are designing a star schema for a sales analysis report. The source data includes Order Details, Products, Customers, and Dates. Which table should be the fact table?

Accepted Answer

Order Details. In a star schema, the fact table stores quantitative, measurable data (metrics) and foreign keys linking to dimension tables. Order Details contains sales transactions with measures like quantity and revenue, making it the correct fact table for sales analysis.

Answer

Dates

Answer

Customers

Answer

Products

Question 6

You have a table with columns 'Product', 'Category', and 'Sales'. You want to create a hierarchy that allows users to drill down from Category to Product. Which is the correct order to create the hierarchy?

Accepted Answer

Category -> Product. In Power BI, a hierarchy is built from the highest (most aggregated) level to the lowest (most granular) level. To allow drill-down from Category to Product, Category must be the top level and Product the child level. Option C correctly orders Category → Product, enabling users to expand from category-level totals to individual product sales.

Answer

Product -> Category -> Sales

Answer

Product -> Category

Answer

Sales -> Product -> Category

Question 7

You have a Power BI data model with a table 'Orders' that has columns: 'OrderID', 'OrderDate', 'CustomerName', 'Region', 'Product', 'Quantity', 'UnitPrice'. You want to create a measure that calculates total sales amount. Which DAX expression should you use?

Accepted Answer

Total Sales = SUMX(Orders, Orders[Quantity] * Orders[UnitPrice]). SUMX is an iterator function that evaluates the expression `Orders[Quantity] * Orders[UnitPrice]` for each row in the Orders table and then sums the results. This is necessary because DAX does not support direct multiplication of two columns inside SUM; SUM expects a single column reference, not an expression. SUMX performs row-by-row evaluation, which correctly computes the total sales amount as the sum of (Quantity × UnitPrice) across all orders.

Answer

Total Sales = COUNTROWS(Orders)

Answer

Total Sales = AVERAGE(Orders[Quantity]) * AVERAGE(Orders[UnitPrice])

Answer

Total Sales = SUM(Orders[Quantity] * Orders[UnitPrice])

Question 8

You are the Power BI administrator for a company that uses Microsoft 365. The security team requires that when a user opens a Power BI report on a personal device, the user must authenticate with Microsoft Entra ID and satisfy a conditional access policy that demands multifactor authentication. The report is in a workspace that is not backed by Fabric capacity. Which feature should you enable to meet this requirement?

Accepted Answer

Microsoft Entra ID Conditional Access. The requirement is to force MFA when users open a report on personal devices. Because Power BI authenticates users through Microsoft Entra ID, a Conditional Access policy that targets the Power BI app and requires MFA will enforce the challenge at sign-in. This works regardless of whether the workspace uses Fabric capacity. Other features like sensitivity labels, RLS, or Embedded do not enforce interactive MFA.

Answer

Power BI Embedded

Answer

Row-level security (RLS)

Answer

Sensitivity labels

Question 9

You have a Power BI model with a table 'Sales' and a related 'Product' table. You want to count the number of distinct products sold. Which DAX expression should you use?

Accepted Answer

DISTINCTCOUNT(Sales[ProductID]). DISTINCTCOUNT(Sales[ProductID]) returns the number of unique ProductID values in the Sales table, which directly answers the requirement to count distinct products sold. This function counts each distinct value in the specified column, ignoring duplicates, and is the standard DAX measure for distinct count calculations.

Answer

COUNTROWS(Sales)

Answer

COUNT(Sales[ProductID])

Answer

COUNTA(Sales[ProductID])

Question 10

You are importing data from a CSV file that contains a column 'OrderDate' with dates in the format 'MM/dd/yyyy'. Some rows have invalid dates like '02/30/2023'. What is the best way to handle these errors in Power Query?

Accepted Answer

Use 'Replace Errors' to replace error values with null.. 'Replace Errors' in Power Query allows you to replace error values (which occur when Power Query fails to convert an invalid date like '02/30/2023' to the Date type) with null. This preserves the rest of the data and keeps the query running without interruption, while clearly marking invalid entries for later handling or analysis.

Answer

Remove rows with errors using 'Remove Rows' > 'Remove Errors'.

Answer

Change the data type to 'Date' and ignore errors.

Answer

Filter the column to exclude rows where the date is invalid after type conversion.

Question 11

Which TWO data sources can be used with DirectQuery mode in Power BI? (Choose two.)

Accepted Answer

SQL Server. DirectQuery mode in Power BI requires a data source that supports query pass-through to a backend engine, and SQL Server (option B) qualifies because Power BI issues native T-SQL queries against the relational database in real time without importing data. Azure SQL Database (option C) is likewise a supported DirectQuery source, since it is a cloud-based SQL Server engine that accepts the same T-SQL query folding and live connection pattern. In contrast, Excel workbook (A), CSV file (D), and SharePoint list (E) are file- or list-based sources that Power BI imports rather than querying live, so they are not valid DirectQuery data sources.

Answer

Excel workbook

Answer

CSV file

Answer

SharePoint list

Question 12

You are a Power BI developer at a healthcare organization. You are building a report that must comply with HIPAA regulations. You need to ensure that patient data is not exposed to unauthorized users. You plan to use Row-Level Security (RLS) with roles defined in Power BI Desktop. However, you also need to limit the data imported into the model to only necessary columns. The source is an Azure SQL Database with a table 'Patients' containing columns: PatientID, Name, SSN, Diagnosis, AdmissionDate, DischargeDate. Which two actions should you take? (Choose TWO)

Accepted Answer

Create RLS roles to restrict access by Diagnosis.. Option A is correct because defining RLS roles in Power BI Desktop and mapping them to users in the Power BI service enforces row-level filtering so that each user only sees the patient rows they are authorized to view, which is a core HIPAA minimum-necessary access control. Option E is correct because removing SSN and Name in Power Query before loading implements data minimization, ensuring sensitive identifiers are never imported into the semantic model where they could be exposed. Option B is not correct because storing credentials in the Power BI service is a connectivity/authentication practice, not a data-exposure control for this scenario. Option C is not correct because disabling query caching does not restrict which data is imported or who can see it. Option D is not correct because an encrypted connection protects data in transit but does not limit imported columns or enforce row-level access for report consumers.

Answer

Store data source credentials in the Power BI service.

Answer

Disable query caching for the dataset.

Answer

Use encrypted connection to the database.

Question 13

You are developing a Power BI semantic model for an e-commerce company. The source data comes from a CSV file containing order details: OrderID, OrderDate, CustomerID, ProductID, Quantity, UnitPrice, Discount, and ShippingCost. The file is updated daily. You need to model the data to support the following analyses: 1) Total sales amount (Quantity * UnitPrice - Discount) by product and month. 2) Average shipping cost per order by customer region (CustomerRegion is in a separate table). 3) Year-over-year comparison of sales. You need to create the measures and ensure optimal performance. What should you do?

Accepted Answer

Import both tables into Power BI, create a date table, and build measures using SUMX and time intelligence.. Importing both tables into Power BI and creating a star schema with a central fact table (Orders) and dimension tables (CustomerRegion, Date) enables efficient measure calculation. The measures can use SUMX to compute sales amount (SUMX(Orders, Orders[Quantity] * Orders[UnitPrice] - Orders[Discount])) and average shipping cost per order filtered by region via relationships. A separate date table is required for time intelligence functions like SAMEPERIODLASTYEAR for year-over-year comparison. Option A is suboptimal because adding calculated columns in Power Query increases storage and processing time; measures are preferable. Option B creates a flat denormalized table which duplicates customer region data, leading to larger model and slower performance. Option C is incorrect because DirectQuery is not supported on CSV files; Power BI requires data import or a connection to a database. Therefore, Option D is the best approach.

Answer

Use Power Query to add a calculated column for sales amount and shipping cost per order, then import.

Answer

Create a single table by appending the customer region to each row in the CSV using Power Query, then import.

Answer

Use DirectQuery on the CSV file to avoid storing data in Power BI.

Question 14

You are merging two queries in Power Query. Query 'Orders' contains columns: OrderID, CustomerID, OrderDate. Query 'Customers' contains columns: CustomerID, CustomerName, Segment. You need to add the CustomerName to the Orders query. The relationship between Orders and Customers is many-to-one. Which join kind should you use?

Accepted Answer

Left Outer. The goal is to retain all rows from the Orders table while adding CustomerName from the Customers table. A Left Outer join returns all rows from the first (left) table and only matching rows from the second (right) table, filling non-matches with null. Since the relationship is many-to-one, each OrderID may have a matching CustomerID, and you want to keep every order even if a customer is missing — exactly what Left Outer does.

Answer

Inner

Answer

Right Outer

Answer

Full Outer

Question 15

Which TWO of the following are valid data source types in Power BI that support DirectQuery? (Select TWO.)

Accepted Answer

Snowflake. Snowflake is a cloud-based data warehouse that supports DirectQuery in Power BI, allowing queries to be sent directly to Snowflake without importing data into Power BI's in-memory engine. This is possible because Snowflake provides a SQL-based interface that Power BI can connect to via its native connector, enabling real-time querying of large datasets.

Answer

Excel workbook

Answer

SharePoint Online List

Answer

JSON file

Question 16

You are a Power BI administrator. A user reports that their scheduled data refresh fails with error 'The data source credentials are no longer valid.' The dataset uses a SQL Server database with Windows authentication. What should you do first to resolve the issue?

Accepted Answer

Ask the user to update the data source credentials in the Power BI service dataset settings.. The first step is to ask the user to update the data source credentials in the Power BI service dataset settings. The error explicitly states that credentials are no longer valid, so refreshing them is the direct fix. This is a common issue when passwords expire or service accounts change.

Answer

Reinstall the on-premises data gateway on the server.

Answer

Reassign the dataset to a different Premium capacity.

Answer

Modify the dataset to use 'Impersonate the authenticated user' for data sources.

Question 17

You are the Power BI administrator for a large enterprise. The company has a Power BI Premium capacity with a single dataset that is used by multiple reports and dashboards. The dataset is refreshed daily at 3:00 AM, and the refresh typically completes within 2 hours. Recently, users have reported that the dataset is not showing the most recent data until after 6:00 AM. You investigate and find that the scheduled refresh is taking 4 hours to complete, and there are no errors in the refresh history. The dataset uses import mode and connects to an on-premises SQL Server data warehouse. The data model contains several large fact tables and multiple calculated tables and measures. What should you do to reduce the refresh time and ensure data is available by 5:00 AM?

Accepted Answer

Implement incremental refresh on the fact tables to refresh only new and changed data. Implementing incremental refresh on the fact tables allows Power BI to refresh only new or changed data instead of the entire dataset each time. This significantly reduces the refresh window, especially for large fact tables, because only the latest partition (e.g., today's data) is processed. Since the scheduled refresh starts at 3:00 AM and must complete by 5:00 AM, incremental refresh can cut the refresh time from 4 hours to under 2 hours by avoiding reprocessing historical data.

Answer

Remove all calculated tables and measures and replace them with calculated columns in Power Query

Answer

Change the dataset storage mode to DirectQuery to avoid the import process

Answer

Install an additional on-premises data gateway and configure load balancing

Question 18

Which TWO actions are required to set up a Power BI deployment pipeline with separate data sources for Development and Production?

Accepted Answer

Define dataset parameters in Power BI Desktop for data source values.. Defining dataset parameters in Power BI Desktop for data source values allows you to make the data source connection dynamic. These parameters can then be overridden at each stage of the deployment pipeline, enabling separate data sources for Development and Production without modifying the report file.

Answer

Assign the dataset owner to each stage workspace.

Answer

Re-enter data source credentials for each stage after deployment.

Answer

Create separate gateways for each stage.

Question 19

You have a Power BI data model with a table that contains duplicate rows. You want to remove duplicates in Power Query. Which transformation should you use?

Accepted Answer

Remove Duplicates. The correct option is B, Remove Duplicates, because it is the Power Query transformation specifically designed to eliminate duplicate rows from a table by comparing all columns (or selected columns) and keeping only the first occurrence of each unique row. In this scenario, the table contains duplicate rows, so applying Remove Duplicates directly addresses the requirement without altering the underlying data values. Replace Values (A) only substitutes specific text or numbers and does not remove rows. Filter Rows (C) excludes rows based on conditions but cannot identify duplicates across all columns. Group By (D) aggregates rows and would change the table structure rather than simply removing duplicate rows.

Answer

Replace Values

Answer

Filter Rows

Answer

Group By

Question 20

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 C is correct because SWITCH(TRUE(), ...) evaluates each condition in order and returns the first TRUE result, so Product[Price] < 10 yields "Low", Product[Price] <= 50 yields "Medium", and the fallback "High" covers prices above 50. This pattern is the standard DAX way to implement multi-branch conditional logic with range comparisons. Option A is wrong because SWITCH with a scalar expression compares for equality, not ranges, so <10 and <=50 are not valid match values. Option B is wrong because LOOKUPVALUE retrieves a value from another table by matching columns and does not perform range-based categorization. Option D is wrong because DAX IF only takes three arguments (condition, true result, false result), so passing five arguments is invalid.

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")