PL-300 Practice Test 4 — 25 Questions

Question 1

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?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use the 'Using Locale' option in the Change Type step to select the appropriate locale (e.g., English (United States)). 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

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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 2

A Power BI report contains a table visual that displays employee names and their total sales. The data model includes an Employee table with columns: EmployeeID, Name, Department, and HireDate. The Sales table has columns: SaleID, EmployeeID, Amount, and SaleDate. The relationship between Employee and Sales is one-to-many. The user wants to see only employees who have made at least one sale. However, the table shows all employees, including those with no sales (blank Amount). What is the most likely reason?

Accepted Answer

There is no visual-level filter to exclude blank values.. The table visual is showing all employees due to the absence of a visual-level filter to exclude blank or zero sales amounts. In Power BI, a one-to-many relationship between Employee and Sales means that employees without sales will still appear in the visual unless explicitly filtered out, as the relationship does not automatically suppress rows from the 'one' side when there are no matching rows on the 'many' side.

Answer

The EmployeeID column in the Employee table is hidden.

Answer

The relationship is many-to-one, not one-to-many.

Answer

The relationship direction is set to Single from Employee to Sales.

Question 3

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. (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

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Dual

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DirectQuery

Question 4

You are building a Power BI semantic model that combines data from an on-premises SQL Server database and a SharePoint Online list. The SQL Server table contains 10 million rows and updates hourly. The SharePoint list contains 500 rows and updates daily. You need to minimize the data load time and ensure the model refreshes within the scheduled 30-minute window. What should you do?

Accepted Answer

Use DirectQuery for the SQL Server table and Import mode for the SharePoint list.. Using DirectQuery for the large SQL Server table (10M rows, hourly updates) avoids importing all rows into the model, significantly reducing data load time and memory usage. Import mode for the small SharePoint list (500 rows, daily updates) is appropriate since it loads quickly and supports full DAX functionality, while the combination keeps the total refresh within the 30-minute window.

Answer

Set both tables to DirectQuery mode.

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Set the SQL Server table to Dual mode and the SharePoint list to Import mode.

Answer

Import both tables into the model and disable incremental refresh.

Question 5

You have a Power BI model with a table named 'Orders' that contains columns: OrderID, CustomerID, OrderDate, and TotalAmount. You need to create a measure that calculates the total sales amount for orders placed in the last 30 days, but only for customers who have placed more than 5 orders in total. What is the most efficient DAX measure?

Accepted Answer

TotalSalesLast30Days = SUMX(FILTER(Orders, Orders[OrderDate] > TODAY() - 30 && CALCULATE(COUNTROWS(Orders), ALLEXCEPT(Orders, Orders[CustomerID])) > 5), Orders[TotalAmount]). It iterates over filtered rows where both conditions are met using a single FILTER and SUMX, which is syntactically valid and more efficient than multiple FILTER iterators. Option B is invalid because KEEPFILTERS expects a filter expression, not a scalar boolean result from CALCULATE(...) > 5.

Answer

TotalSalesLast30Days = CALCULATE(SUM(Orders[TotalAmount]), FILTER(Orders, Orders[OrderDate] > TODAY() - 30), FILTER(Orders, CALCULATE(COUNTROWS(Orders), ALLEXCEPT(Orders, Orders[CustomerID])) > 5))

Answer

TotalSalesLast30Days = CALCULATE(SUM(Orders[TotalAmount]), KEEPFILTERS(Orders[OrderDate] > TODAY() - 30), KEEPFILTERS(CALCULATE(COUNTROWS(Orders), ALLEXCEPT(Orders, Orders[CustomerID])) > 5))

Answer

TotalSalesLast30Days = CALCULATE(SUM(Orders[TotalAmount]), DATESINPERIOD(Orders[OrderDate], TODAY(), -30, DAY))

Question 6

You have a data model with a Sales table and a Date table. You create a measure: Total Sales = SUM(Sales[Amount]). When you add a slicer for Date[Year], the measure does not filter correctly. What is the most likely cause?

Accepted Answer

The relationship is inactive. The most likely cause is that the relationship between the Sales table and the Date table is inactive. In Power BI, only one active relationship can exist between two tables; any additional relationships must be inactive. A slicer on Date[Year] will only filter through the active relationship. If the active relationship is not the one intended for the measure, the slicer will not affect the measure's result. Using USERELATIONSHIP in the measure or setting the correct relationship as active would resolve this.

Answer

The Date table is not marked as a date table

Answer

The Sales table has no relationship to the Date table

Answer

The measure uses SUM instead of SUMX

Question 7

You are reviewing the partition configuration for a Power BI Import model as shown in the exhibit. The table Sales is partitioned by year. You need to modify the model to improve incremental refresh performance. What change should you make?

Accepted Answer

Configure incremental refresh policy. Configuring an incremental refresh policy (Option B) is the correct approach because it automatically manages partition creation and refresh for the Sales table based on a date/time column. This improves performance by refreshing only the most recent data (e.g., last 5 years) while keeping historical partitions unchanged, reducing refresh time and resource consumption compared to manual yearly partitions.

Answer

Increase the number of partitions to monthly

Answer

Remove all partitions and load data as a single table

Answer

Change the storage mode to DirectQuery

Question 8

You are designing a Power BI solution that ingests data from multiple sources: Azure Blob Storage, Salesforce, and an on-premises Oracle database. The data must be combined into a single semantic model. The Oracle database contains sensitive customer information that must be masked before being loaded. Which approach should you use to prepare the data?

Accepted Answer

Create a Power BI dataflow that extracts, transforms, and masks data before loading into the semantic model. Power BI dataflows provide a cloud-based ETL solution that can connect to Azure Blob Storage, Salesforce, and on-premises Oracle (via an on-premises data gateway), perform transformations including data masking, and then load the prepared data into a shared semantic model. This approach centralizes data preparation, ensures sensitive data is masked before any downstream consumption, and supports scheduled refreshes without requiring additional infrastructure.

Answer

Use DirectQuery to connect to all sources and rely on database-level masking

Answer

Import all data into Power BI Desktop and apply transformations in the Power Query Editor

Answer

Stage the data in an Azure SQL Database and use SQL Server Analysis Services to mask data

Question 9

You are building a star schema model in Power BI. You have a fact table of sales transactions and dimension tables for Date, Customer, Product, and Store. The Date table contains a column 'FiscalYear' that you want to use for time intelligence calculations. What is the best practice for handling the Date relationship?

Accepted Answer

Mark the Date table as a date table using the Calendar icon in the Table tools ribbon and set a relationship on the Date column.. Marking the Date table as a date table (via the Calendar icon in Table tools) and creating a relationship on the Date column is the best practice for time intelligence in Power BI. This ensures that DAX time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) work correctly by using a single, continuous date column that aligns with the fact table's date column. It also avoids the need for composite keys or separate fiscal tables, maintaining a clean star schema.

Answer

Create a separate fiscal date table and relate it to the fact table using the FiscalYear column.

Answer

Use the built-in DATESYTD function directly on the OrderDate column from the fact table.

Answer

Create a composite key using FiscalYear and Quarter columns in the Date table and relate to the fact table.

Question 10

You are importing data from a SQL Server view into Power BI. The view contains calculated columns that are expensive to compute. You want to minimize the load on the source database during refresh. What should you do?

Accepted Answer

Import the raw data and perform transformations in Power Query.. Importing raw data and performing transformations in Power Query offloads the computational burden from the SQL Server source to Power BI's mashup engine. This minimizes load on the source database during refresh, as expensive calculated columns are not executed on SQL Server. Power Query can apply transformations after the data is extracted, reducing the need for server-side processing.

Answer

Enable query folding to push transformations to SQL Server.

Answer

Use a native SQL query in Power Query to perform calculations.

Answer

Create a materialized view in SQL Server with the calculations.

Question 11

You are reviewing a Power Query M expression that transforms column types. The 'SalesAmount' column contains values like '1,234.56' (with a comma as thousands separator). After applying this transformation, what is the likely result?

Accepted Answer

The transformation will result in errors for rows containing commas.. Power Query's default type conversion for numeric columns expects a period as the decimal separator and no thousands separator. When the 'SalesAmount' column contains values like '1,234.56' with a comma as a thousands separator, attempting to convert the column directly to a number type (e.g., using 'Change Type' or 'Table.TransformColumnTypes') will cause errors for rows containing commas, as Power Query cannot parse the comma as part of a valid number. The comma is not a recognized numeric character in the default locale, so the conversion fails.

Answer

The column will be converted to text automatically.

Answer

The column will be successfully converted to numbers.

Answer

The transformation will ignore the comma and convert the number correctly.

Question 12

A Power BI report includes a bar chart showing total sales by product category. The report designer wants to add a trend line to the chart to show the overall sales trend over time. Which type of visual should be used instead?

Accepted Answer

Line chart. A line chart is the correct visual to show a trend over time because it plots data points connected by straight lines, making it easy to see the overall direction and pattern of total sales across a continuous time axis. Bar charts, including stacked variants, are designed for comparing discrete categories, not for displaying continuous trends.

Answer

Stacked bar chart

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Scatter chart

Answer

Pie chart

Question 13

Which TWO actions can you perform using Power BI Desktop's Query Editor? (Choose two.)

Accepted Answer

Merge two tables based on a common column.. In Power BI Desktop's Query Editor, you can merge two tables based on a common column using the 'Merge Queries' feature (option B) and remove duplicate rows using the 'Remove Duplicates' feature (option D). Creating a relationship between tables (option C) is not performed in Query Editor; it is done in the Model view after loading data. Defining row-level security roles (option A) and creating DAX measures (option E) are also not available in Query Editor — roles are managed in the Modeling tab or Power BI Service, and measures are created in the Report or Data view.

Answer

Define row-level security (RLS) roles.

Answer

Create a relationship between two tables.

Answer

Create a new measure using DAX.

Question 14

You have a Power BI model with a table named Orders that contains columns OrderDate, ShipDate, and CustomerID. You need to create a calculated column that computes the number of days between OrderDate and ShipDate. Which DAX expression should you use?

Accepted Answer

DATEDIFF(Orders[OrderDate], Orders[ShipDate], DAY). The DATEDIFF function in DAX calculates the interval between two dates in the specified unit (DAY). This directly computes the number of days between OrderDate and ShipDate, which is the required result for the calculated column.

Answer

DATEADD(Orders[OrderDate], 1, DAY)

Answer

DAY(Orders[ShipDate] - Orders[OrderDate])

Answer

NETWORKDAYS(Orders[OrderDate], Orders[ShipDate])

Question 15

You are designing a Power BI model that includes a fact table with sales data and a dimension table for customers. Each customer can have multiple addresses, but you only need the primary address for analysis. The source system has a 'CustomerAddress' table with a 'IsPrimary' flag. What is the best approach to bring this into the model?

Accepted Answer

In Power Query, filter the CustomerAddress table to only include rows where IsPrimary = True, then merge with Customer.. It uses Power Query to filter the CustomerAddress table to only primary addresses before merging with the Customer dimension. This ensures that only the necessary rows are imported into the model, reducing data volume and avoiding complex DAX or relationship overhead. The result is a clean, single-row-per-customer dimension that directly supports analysis without runtime filtering.

Answer

Use a DAX measure to filter the address table dynamically.

Answer

Import the entire CustomerAddress table and create an active relationship on the CustomerID column.

Answer

Create a calculated table using SUMMARIZE to get the primary address per customer.

Question 16

You are analyzing a DAX query as shown in the exhibit. You need to determine the result set. The model contains tables: Date, Product, and Sales with relationships. Which statement accurately describes the output?

Accepted Answer

The query returns total sales per year and category for Amount > 100. The DAX query uses SUMMARIZECOLUMNS to group sales by 'Year' from the Date table and 'Category' from the Product table, then filters the Sales table to include only rows where Amount > 100. The result is a table of total sales (sum of Amount) for each combination of year and category that meets the filter condition.

Answer

The query returns total sales for each year, ignoring category

Answer

The query returns sales amounts only for products with Amount > 100

Answer

The query returns total sales for each category, ignoring year

Question 17

You are importing data from a CSV file that contains a column with mixed data types (numbers and text). Power BI automatically assigns the data type as Text. You need to perform numerical aggregations on this column. What should you do?

Accepted Answer

In Power Query Editor, change the data type of the column to Whole Number or Decimal Number.. Changing the column's data type to Whole Number or Decimal Number in Power Query Editor will force Power BI to interpret the numeric values as numbers, enabling aggregations like SUM or AVERAGE. Power Query Editor provides a robust transformation environment where data type changes are applied during the load process, ensuring the column is treated as numeric for all downstream calculations. This approach is more efficient and reliable than using DAX conversions, as it avoids the overhead of calculated columns and leverages Power Query's native type detection and error handling.

Answer

Split the column using a delimiter to separate numbers from text.

Answer

Create a relationship with a numeric table to enable aggregation.

Answer

Create a calculated column in DAX using VALUE() to convert the text to numbers.

Question 18

You are reviewing the deployment configuration for a Power BI dataset. The exhibit shows a JSON snippet of the dataset settings. You need to ensure that data is refreshed twice a day at 6:00 AM and 6:00 PM UTC. However, the refresh fails at both scheduled times. What is the most likely cause?

Accepted Answer

The data source uses Integrated Security (SSPI) which is not supported for scheduled refresh.. Scheduled refresh in Power BI requires a gateway to connect to on-premises data sources, and when the data source uses Integrated Security (SSPI), the gateway cannot delegate credentials for scheduled refresh. SSPI relies on the user's interactive Windows authentication context, which is not available during unattended scheduled refresh operations. This causes the refresh to fail at both scheduled times.

Answer

The refresh schedule uses UTC but the data source is in a different time zone.

Answer

The dataset has DirectQuery enabled, which prevents Import mode refresh.

Answer

The gateway ID is incorrect.

Question 19

You are building a Power BI report for a manufacturing company. You have a large fact table with 50 million rows in Azure SQL Database. You need to minimize the data refresh time and ensure that only new or changed rows are loaded. The source table has a LastModifiedDate column. What should you do?

Accepted Answer

Configure incremental refresh on the table using the LastModifiedDate column.. Incremental refresh in Power BI allows you to load only new or changed rows from a large fact table by filtering on a date/time column such as LastModifiedDate. This minimizes data refresh time by avoiding a full reload of all 50 million rows, and it leverages the source system's ability to efficiently query only the modified data. Power Query pushes the filter logic to Azure SQL Database via query folding, ensuring optimal performance.

Answer

Enable query folding in Power Query to push filters to the source.

Answer

Schedule a full refresh every hour.

Answer

Create a Power BI dataflow that performs a full load and then use that dataflow as a source.

Question 20

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model includes a large fact table with 100 million rows. Users are experiencing slow report performance. Which TWO actions should the developer take to improve query performance?

Accepted Answer

Create indexes on columns used in filters and relationships.. In DirectQuery mode, incremental refresh is not supported (option A is incorrect). Creating indexes on columns used in filters and relationships (option B) speeds up query execution on SQL Server. Removing unused columns from the fact table (option C) reduces the amount of data transferred per query. Hiding columns (option D) does not affect the data retrieved by queries. Adding calculated columns (option E) increases query overhead and degrades performance.

Answer

Configure incremental refresh to limit data retrieved per query.

Answer

Hide columns that are not needed in reports.

Answer

Add calculated columns to precompute aggregations.