PL-300 Practice Exam 57 — 20 Questions

Question 1

You are designing a Power BI data model for a sales analytics solution. The source data includes a 'Sales' fact table with millions of rows and dimension tables for 'Customer', 'Product', 'Date', and 'Salesperson'. You need to minimize the model size in Power BI. Which action should you take?

Accepted Answer

Remove any columns from the fact table that are not used in the model.. Removing unused columns from the fact table reduces the amount of data imported into the VertiPaq engine, which directly minimizes the model size. Each column consumes memory for compression and storage, so eliminating unnecessary columns is the most effective way to reduce the model footprint without changing query performance or data refresh behavior.

Answer

Set the 'Storage mode' of fact table to 'DirectQuery'.

Answer

Enable 'Include relationship columns' in the relationship settings.

Answer

Create a calculated column for row number.

Question 2

You need to connect Power BI to an Excel file stored on a local network drive. The file is updated manually each morning. You want the Power BI report to always show the latest data when opened. Which data connectivity mode should you choose?

Accepted Answer

Import. Option C (Import) is correct because Power BI must load the Excel data into its internal VertiPaq engine to support the full range of transformations and visualizations. Since the file is on a local network drive and updated manually, Import mode allows you to refresh the dataset on demand or via a scheduled refresh, ensuring the report always shows the latest data when opened. DirectQuery and Live Connection are not applicable because they require a live queryable data source (like SQL Server or Analysis Services), not a flat file.

Answer

Live Connection

Answer

Dual

Answer

DirectQuery

Question 3

You are importing data from a CSV file into Power BI. The file contains a column 'Price' with values like '$1,234.56'. When you preview the data, the column is recognized as text. You need to convert it to a decimal number. What should you do in Power Query Editor?

Accepted Answer

Replace values: remove '$' and ',' then change type to Decimal Number.. Option A is correct because Power Query Editor cannot automatically parse currency-formatted text like '$1,234.56' into a decimal number due to the non-numeric characters. By first using Replace Values to remove the '$' and ',' symbols, you strip the text down to '1234.56', which Power Query can then successfully convert to a Decimal Number type using the Change Type step.

Answer

Split the column by delimiter and keep the numeric part.

Answer

Change the data type to Decimal Number directly.

Answer

Remove commas using Replace Values, then change type.

Question 4

You are using Power Query to combine data from multiple CSV files in a folder. Each file has the same structure. You want to append all rows into a single table. Which Power Query function should you use?

Accepted Answer

Combine Files from the folder connector.. Option D is correct because the 'Combine Files' transformation in Power Query is specifically designed to import and append multiple CSV files from a folder into a single table. When you connect to a folder using the 'From Folder' connector, Power Query automatically generates a 'Combine Files' step that uses the 'Table.Combine' function under the hood, which appends all rows from identically structured files into one unified table.

Answer

Group By.

Answer

Append Queries.

Answer

Merge Queries as new.

Question 5

You are reviewing a Power BI data source configuration for an Azure SQL Database. The connection uses OAuth2 authentication. However, when scheduling a refresh, the refresh fails with an error that authentication fails. What is the most likely cause?

Accepted Answer

The authority URL should point to the specific Azure AD tenant, not 'common'. When using OAuth2 authentication with Azure SQL Database in Power BI, the authority URL must point to the specific Azure AD tenant (e.g., 'https://login.microsoftonline.com/your-tenant-id') rather than the generic 'common' endpoint. The 'common' endpoint is designed for multi-tenant applications and cannot resolve the tenant-specific authentication context required for scheduled refreshes, leading to authentication failures.

Answer

The connection string has 'Encrypt=True' which is incompatible with OAuth2

Answer

The server name in the connection string is incorrect

Answer

The resource URL should be 'https://management.azure.com/'

Question 6

You are importing a large CSV file (200 MB) into Power BI Desktop. The import is very slow and sometimes fails. What should you do to improve performance?

Accepted Answer

Filter rows and columns during import using Power Query to reduce data size.. Option C is correct because filtering rows and columns during import using Power Query reduces the data volume loaded into the Power BI Desktop model, directly addressing the root cause of slow imports and failures when handling a 200 MB CSV file. Power Query's query folding capabilities push data reduction operations (e.g., removing unnecessary columns, filtering rows based on conditions) upstream, minimizing memory and processing overhead during the import phase. This approach is a standard best practice for optimizing data ingestion in Power BI Desktop, especially for large flat files.

Answer

Use Power BI Service to import the file instead.

Answer

Remove all relationships before import.

Answer

Upgrade to Power BI Premium.

Question 7

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. Option A is correct because `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 8

Which TWO are valid ways to combine data from multiple sources in Power Query? (Choose two.)

Accepted Answer

Append Queries.. Option B is correct because the Append Queries operation in Power Query combines rows from two or more tables by stacking them vertically, which is a standard way to consolidate data from multiple sources when the columns are aligned. This is distinct from merging, which combines columns based on matching keys.

Answer

Pivot Column.

Answer

Create relationships in the data model.

Answer

Group By.

Question 9

Which THREE of the following are best practices when preparing data in Power BI for optimal performance?

Accepted Answer

Set correct data types for all columns.. Setting correct data types for all columns (Option C) is a best practice because it ensures that Power BI uses the most efficient storage and processing methods. Incorrect data types can lead to increased memory usage, slower query performance, and inaccurate calculations, as Power BI must perform implicit conversions at query time.

Answer

Merge all tables into a single table for simplicity.

Answer

Create calculated columns instead of measures when possible.

Question 10

You are importing a CSV file into Power BI. The file contains a date column with values in the format 'MM/dd/yyyy'. However, Power Query interprets the dates as 'dd/MM/yyyy'. What should you do to correctly parse the dates?

Accepted Answer

Use the 'Using Locale' option in the Change Type step to select the appropriate locale (e.g., English (United States)). Option B is correct because Power Query's 'Using Locale' option in the Change Type step allows you to specify the regional format of the source data (e.g., English (United States) for 'MM/dd/yyyy'). This overrides Power Query's default locale-based interpretation, ensuring dates are parsed correctly without altering the data or system settings.

Answer

Change the system region settings of the Power BI service to US

Answer

Change the column data type to Text and then manually replace separators

Answer

Split the column into day, month, and year, then combine them in the correct order

Question 11

You have a Power BI dataset that uses a live connection to an Analysis Services tabular model. The model contains a measure that uses the ALL function. You need to create a report page that shows sales by region, but you want to display the percentage of total sales regardless of region filter. How should you achieve this?

Accepted Answer

Use the existing measure and add a visual-level filter to show percentage.. Option B is correct because with a live connection to Analysis Services, you cannot modify the underlying measure in Power BI; you must work with the existing measures. By using the existing measure and adding a visual-level filter to show the percentage (e.g., by using the 'Show value as' option set to 'Percent of grand total'), you can display the percentage of total sales regardless of the region filter without altering the model.

Answer

Modify the measure in the Analysis Services model to use ALLSELECTED instead of ALL.

Answer

Change the connection to Import mode and then create the measure.

Answer

Create a new measure in the Power BI dataset using DAX that divides the region sales by total sales.

Question 12

You need to combine two tables: Sales and Products, where Sales has a ProductID column and Products has a ProductKey column. The tables have a many-to-one relationship. Which Power Query transformation should you use?

Accepted Answer

Merge Queries.. Merge Queries (C) is correct because it performs a join between two tables based on matching columns, which is exactly what is needed to combine Sales and Products using ProductID and ProductKey. This transformation supports many-to-one relationships and allows you to expand related columns from the Products table into the Sales table, enabling further data analysis.

Answer

Group By.

Answer

Append Queries.

Answer

Pivot Column.

Question 13

You are importing data from a CSV file into Power BI. The file contains a column 'SalesAmount' with values like '1,234.56' and '(987.65)' for negative amounts. You need to transform this column into a decimal number. Which sequence of Power Query steps achieves this?

Accepted Answer

Replace Values ('(' with '-'), Replace Values (')' with ''), Replace Values (',' with ''), then Change Type to Decimal. Option D is correct because it first removes the comma thousands separator, then replaces the opening parenthesis with a minus sign, removes the closing parenthesis, and finally changes the data type to Decimal. This sequence ensures that the negative indicator is properly placed before the numeric value and that the string is cleanly formatted for type conversion.

Answer

Change Type to Decimal, then Replace Values (',' with ''), then Replace Values ('(' with '-')

Answer

Replace Values (',' with ''), then Replace Values ('(' with '-'), then Replace Values (')' with ''), then Change Type to Decimal

Answer

Replace Values (',' with ''), Change Type to Decimal, then Replace Values ('(' with '-')

Question 14

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 15

Which TWO actions should you take to reduce the size of a Power BI dataset? (Choose two.)

Accepted Answer

Filter out rows that are not needed.. Option A is correct because filtering out unnecessary rows at the source reduces the number of rows loaded into the Power BI dataset, directly decreasing the data volume and storage size. This is a fundamental data reduction technique that minimizes memory consumption and improves refresh performance.

Answer

Disable query folding to improve performance.

Answer

Add calculated columns to precompute values.

Answer

Use DirectQuery instead of Import.

Question 16

Refer to the exhibit. You are configuring a data source in Power BI Service using a JSON policy. The data source fails to refresh. What is the most likely issue?

Accepted Answer

The service principal does not have permission to the Azure SQL Database.. Option A is correct because when using a JSON policy with a service principal in Power BI, the service principal must have the necessary permissions (e.g., db_datareader role) on the Azure SQL Database. Without these permissions, the data source will fail to refresh, as Power BI cannot authenticate or access the data. The JSON policy itself may be syntactically valid, but the underlying authentication fails due to insufficient database-level permissions.

Answer

The version value should be "2.0".

Answer

The JSON is missing the 'dataSource' type.

Answer

The connection string is missing the database name.

Question 17

You need to combine two tables from different sources: 'Orders' from SQL Server and 'Returns' from an Excel file. Both tables have a column named 'OrderID'. You want to include all orders and only matching returns. Which join type should you use in Power Query?

Accepted Answer

Left Outer Join. In Power Query, a Left Outer Join returns all rows from the first (left) table ('Orders') and only the matching rows from the second (right) table ('Returns'), based on the 'OrderID' column. This matches the requirement to include all orders and only matching returns, ensuring no order is dropped even if it has no corresponding return.

Answer

Inner Join

Answer

Right Outer Join

Answer

Full Outer Join

Question 18

Which TWO of the following are valid ways to create a date table in Power BI?

Accepted Answer

Using DAX function CALENDAR or CALENDARAUTO.. Option D is correct because the DAX functions CALENDAR and CALENDARAUTO are specifically designed to generate a single-column table of dates, which can then be used as a date table. CALENDAR requires explicit start and end dates, while CALENDARAUTO automatically scans the model to determine the date range. Both are standard methods for creating a date table in Power BI.

Answer

Using the time intelligence functions like TOTALYTD.

Answer

Marking an existing table as a date table.

Answer

Enabling the auto date/time feature.

Question 19

Which TWO of the following are valid methods to combine data from multiple sources in Power BI?

Accepted Answer

Append Queries. Append Queries is a valid method to combine data from multiple sources in Power BI because it stacks rows from two or more tables into a single table, which is essential when you have similar data structures across different sources (e.g., monthly sales files). This operation is performed in Power Query Editor and corresponds to a UNION operation in SQL, making it a standard data preparation technique.

Answer

Pivot Column

Answer

Unpivot Columns

Answer

Group By

Question 20

You are reviewing the DAX expression above. The DateTable is supposed to have a continuous date range from 2020 to 2025. However, when you use the Year column in a slicer, the data shows only 2024 values. What is the most likely cause?

Accepted Answer

The DateTable is not related to the fact table.. Option C is correct because the slicer showing only 2024 values indicates that the DateTable is not related to the fact table. Without an active relationship, the slicer on the Year column cannot filter the fact table, so it defaults to showing only the current year (2024) or the first year in the DateTable. A proper relationship (e.g., one-to-many from DateTable[Date] to FactTable[Date]) is required for cross-filtering to work.

Answer

The ADDCOLUMNS function is not supported.

Answer

The DAX syntax for CALENDAR is incorrect.

Answer

The DateTable has too many rows.