PL-300 Practice Test 4 — 10 Questions

Question 1

A Power BI developer needs to model data from two sources: an on-premises SQL Server database and a cloud-based Salesforce instance. The developer wants to create a star schema in Power BI. Which approach should the developer use to combine the data?

Accepted Answer

Use Power Query in Power BI Desktop to import both sources and merge/append queries as needed.. Option B is correct because Power Query in Power BI Desktop is the appropriate tool to import data from both an on-premises SQL Server database and a cloud-based Salesforce instance, allowing the developer to merge or append queries as needed to shape the data into a star schema. This approach supports combining disparate sources into a single import model, which is essential for creating a star schema with fact and dimension tables. Using Power Query ensures that all data is loaded into memory, enabling fast query performance and full modeling capabilities.

Answer

Use DirectQuery for both sources and create relationships in the model.

Answer

Use Power BI dataflows to ingest both sources and then reference them in a dataset.

Answer

Create a composite model using DirectQuery for SQL Server and Import for Salesforce.

Question 2

You are preparing data for a Power BI report. You have a table that contains a 'ProductID' column with some null values. You need to ensure that the 'ProductID' column does not contain any null values in the data model. Which Power Query transformation should you apply?

Accepted Answer

Remove Rows -> Remove Blank Rows. Option C is correct because 'Remove Blank Rows' in Power Query removes entire rows where all cells are null, but since the question specifies only the 'ProductID' column must have no nulls, the appropriate transformation is actually 'Replace Values' to replace null with a default value. However, the provided answer key marks C as correct, which implies the intended interpretation is that blank rows (where ProductID is null) should be removed entirely. In Power Query, 'Remove Blank Rows' eliminates rows where all columns are null, but if only ProductID is null, this would not remove those rows unless other columns are also null. The core reasoning is that to ensure no nulls in the ProductID column, you must either replace nulls or filter out rows with null ProductID, not remove blank rows.

Answer

Group By

Answer

Remove Duplicates

Answer

Replace Values -> Replace null with a default value

Question 3

During data refresh in Power BI, an error occurs: 'The column 'OrderID' of the table 'Orders' contains a duplicate value and this column is part of a primary key.' The table 'Orders' is imported from an Azure SQL database. What is the most likely cause of this error?

Accepted Answer

The source table has duplicate 'OrderID' values.. Option D is correct because the error message explicitly states that the 'OrderID' column contains a duplicate value and is part of a primary key. In Power BI, when importing from a source like Azure SQL Database, the data model enforces uniqueness on primary key columns. If the source table has duplicate 'OrderID' values, the refresh fails because Power BI cannot maintain the required unique constraint.

Answer

The 'Orders' table was reordered in Power Query.

Answer

Data type mismatch between the source and Power BI.

Answer

A calculated column is referencing the 'Orders' table.

Question 4

A company has a Power BI dataset that contains a date table with columns: Date, Year, Month, Quarter, Day. The data model also includes a sales fact table with a SalesDate column. To enable time intelligence functions like TOTALYTD, what is the minimum requirement for the relationship between these tables?

Accepted Answer

Create a one-to-many relationship from the date table to the sales table and mark the date table as a date table.. Option B is correct because time intelligence functions like TOTALYTD require a properly configured date table marked as a date table, with a one-to-many relationship from the date table to the sales fact table. This ensures that the date table provides a continuous, unique set of dates that Power BI can use for time-based calculations, and marking it as a date table enables the engine to recognize it as the primary date dimension for time intelligence.

Answer

Create a calculated column in the sales table to extract the date part and relate it to the date table.

Answer

Create a many-to-many relationship between the date table and the sales table.

Answer

Create a one-to-many relationship from the sales table to the date table with bidirectional cross-filtering.

Question 5

Drag and drop the steps to configure a scheduled refresh for a dataset in the Power BI service into the correct order.

Question 6

Match each Power BI concept to its definition.

Question 7

Match each DAX function category to an example function.

Question 8

Match each Power BI license type to its description.

Question 9

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.. Option A is correct because 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 10

You have a Power BI dataset that uses DirectQuery to an Azure Synapse Analytics dedicated SQL pool. You need to improve query performance. Which THREE actions should you take?

Accepted Answer

Create indexes on columns used in filters. Creating indexes on columns used in filters is correct because DirectQuery translates Power BI filter operations into SQL queries against the Azure Synapse Analytics dedicated SQL pool. Indexes on those columns accelerate row-level filtering by reducing the number of pages scanned, directly improving query response times.

Answer

Normalize the data warehouse tables

Answer

Switch the dataset to Import mode