PL-300 Practice Test 9 — 10 Questions

Question 1

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?

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

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

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The Sales table has no relationship to the Date table

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The measure uses SUM instead of SUMX

Question 2

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

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Remove all partitions and load data as a single table

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Change the storage mode to DirectQuery

Question 3

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

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

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

Question 4

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.

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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 5

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.

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

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Create a materialized view in SQL Server with the calculations.

Question 6

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.

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The column will be successfully converted to numbers.

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

Question 7

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

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Pie chart

Question 8

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 9

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])

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

Question 10

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.

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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.