PL-300 Practice Exam 3 — 20 Questions

Question 1

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 2

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 3

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 4

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 5

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 6

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 7

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 8

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 9

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 10

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")

Question 11

You need to create a relationship between two tables in Power BI. Both tables contain a column named 'ProductID', but the values in one table are integers and in the other are text. What should you do first?

Accepted Answer

Ensure both columns have the same data type, either by changing the data type in Power Query or in the model view.. In Power BI, relationships require matching data types on both sides of the key columns. If one 'ProductID' column is integer and the other is text, the relationship engine cannot resolve the join because the data types are incompatible. Changing both columns to the same data type—either in Power Query (recommended for performance) or in the model view—resolves this mismatch and allows a valid relationship to be created.

Answer

Merge the two tables into one in Power Query.

Answer

Create a new calculated column that converts the integer to text using FORMAT.

Answer

Set the relationship to 'Many-to-many' to bypass the type mismatch.

Question 12

A data analyst creates a Power BI report using a dataset that contains sensitive salary information. The analyst needs to ensure that only HR managers can see salary columns. What should the analyst use?

Accepted Answer

Object-level security (OLS).. Object-level security (OLS) is the correct choice because it restricts access to specific tables or columns within a dataset, which is exactly what is needed to hide salary columns from everyone except HR managers. OLS is defined in the dataset's Tabular Model roles and can deny access to individual columns so that unauthorized users cannot see them in reports. Row-level security (RLS) only filters rows, not columns, so it cannot prevent viewing salary columns. Microsoft Purview sensitivity labels classify and protect data but do not control column visibility in Power BI reports, and 'Restrict access' is not a valid dataset security setting for column-level control.

Answer

Row-level security (RLS).

Answer

Microsoft Purview sensitivity labels.

Answer

Set the dataset security to 'Restrict access'.

Question 13

You are preparing a Power BI dataset that will be used by report authors. The source data contains a column named 'CustomerName' with leading and trailing spaces. You need to remove these spaces in Power Query. Which transformation should you use?

Accepted Answer

Trim. The Trim transformation is specifically designed to remove leading and trailing whitespace from text values. It preserves internal spaces, ensuring names remain intact. Other transformations either target different issues or would alter the data incorrectly. Using Trim is the standard and correct way to clean this column in Power Query.

Answer

Split Column

Answer

Replace Values

Answer

Clean

Question 14

You need to create a measure that calculates year-over-year growth percentage. Which DAX function should you use?

Accepted Answer

SAMEPERIODLASTYEAR. SAMEPERIODLASTYEAR is the most direct and semantically clear function for year-over-year comparisons because it returns the same period in the prior year without requiring complex interval arguments. While DATEADD('Date'[Date], -1, YEAR) produces the same result, SAMEPERIODLASTYEAR is specifically designed for this purpose and is easier to read. PARALLELPERIOD, on the other hand, shifts entire periods and may not align with the current granularity (e.g., a monthly context would return the full prior year).

Answer

DATEADD

Answer

DATESYTD

Answer

PARALLELPERIOD

Question 15

You are connecting to a SharePoint folder that contains Excel workbooks. Each workbook has multiple sheets. You need to combine data from a specific sheet named 'Sales' across all workbooks. Which Power Query approach should you use?

Accepted Answer

Use the SharePoint folder connector, filter by .xlsx, then expand the Content column and filter by sheet name 'Sales'.. The SharePoint folder connector retrieves all files in the folder, including Excel workbooks. By filtering for .xlsx files and then expanding the Content column, you access the binary data of each workbook. You can then filter by the 'Sales' sheet name to combine data from that specific sheet across all workbooks, which is the only approach that directly handles multiple workbooks with multiple sheets.

Answer

Use the SharePoint Online List connector and select the document library.

Answer

Use the Excel connector and specify the folder path.

Answer

Use the Web connector and provide the SharePoint site URL.

Question 16

You have a Power BI model with a 'Date' table marked as a date table. You need to create a measure that calculates the running total of sales over the last 12 months. Which DAX function should you use?

Accepted Answer

DATESINPERIOD. DATESINPERIOD, is correct because it allows you to define a dynamic window of dates—specifically, the last 12 months ending with the latest date in the current filter context. When used with a measure like CALCULATE(SUM(Sales[Amount]), DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -12, MONTH)), it shifts the date range backward by 12 months from the last visible date, making it ideal for a rolling 12-month total. The 'Date' table being marked as a date table ensures that time intelligence functions respect the continuous date range.

Answer

PREVIOUSYEAR

Answer

DATESYTD

Answer

DATEADD

Question 17

You have a Power BI dataset that uses Import mode and refreshes daily. The source data includes a column 'LastModifiedDate'. You want to reduce the amount of data loaded during each refresh by only loading rows that have changed since the last refresh. Which feature should you configure?

Accepted Answer

Configure incremental refresh on the table using the 'LastModifiedDate' column.. Incremental refresh in Power BI allows you to filter data by a date/time column (such as 'LastModifiedDate') so that only rows that have changed since the last refresh are loaded. This reduces refresh time and data volume while still using Import mode. The feature requires a date/time column and a properly configured policy in the Power Query Editor.

Answer

Enable query folding in Power Query.

Answer

Use the 'Reduce data' option in Power Query Editor.

Answer

Change the storage mode to DirectQuery.

Question 18

Refer to the exhibit. You are reviewing a Power BI data source credential configuration. The Azure Blob Storage data source uses 'Anonymous' credentials. However, the refresh fails with an error indicating that the blob container is private and requires authentication. Which change should you make?

Accepted Answer

Change credential type to 'Account Key' and provide the storage account key.. Azure Blob Storage containers that are private require authentication. The 'Account Key' credential type in Power BI uses the storage account key to authenticate via the Azure Storage REST API, which is the correct method for accessing private blob containers. Anonymous access only works when the container is configured for public access.

Answer

Change credential type to 'Service Principal' and provide the app ID and secret.

Answer

Change credential type to 'Basic' and provide the storage account name and key.

Answer

Change credential type to 'Windows' for the Azure Blob datasource.

Question 19

You are reviewing a Power BI data source configuration JSON. The exhibit shows a data source definition. What is the privacy level setting for the data source 'SalesData'?

Accepted Answer

Private. The privacy level setting for the data source 'SalesData' is 'Private' because the JSON snippet shows the property "privacyLevel":"Private". In Power BI, the Private privacy level restricts data from being combined with data from other sources, ensuring that sensitive data is not inadvertently shared across queries. This setting is explicitly defined in the data source configuration and is not Organizational, None, or Public.

Answer

Organizational

Answer

None

Answer

Public

Question 20

You are importing data from a folder containing multiple CSV files with identical structure. You want to automatically combine all files into one table in Power Query. Which connector should you use?

Accepted Answer

Folder connector. The Folder connector is the correct choice because it is specifically designed to connect to a folder containing multiple files, and when combined with the 'Combine Files' transformation in Power Query, it automatically merges all CSV files with identical structures into a single table. This connector handles the iterative process of reading each file and appending rows without manual scripting.

Answer

Excel Workbook connector

Answer

CSV connector

Answer

Web connector