PL-300 Practice Test 17 — 15 Questions

Question 1

You need to grant a user the ability to manage permissions on a Power BI workspace but not to view or edit the content. What minimum role should you assign?

Accepted Answer

Admin. The Admin role is the only workspace role that can manage permissions and membership, even though it also allows viewing and editing content. The minimum role required to manage permissions is Admin. Option A is incorrect because Contributor can view and edit content but cannot manage permissions. Option B is incorrect because Viewer can only view content and cannot manage permissions. Option C is incorrect because Member can view and edit content but cannot manage permissions.

Answer

Contributor

Answer

Viewer

Answer

Member

Question 2

A data model contains a table 'Sales' with columns: Date, ProductID, Quantity, Amount. There is a 'Products' table with columns: ProductID, ProductName, CategoryID. A measure 'Total Sales' = SUM(Sales[Amount]) returns correct values. However, when a user creates a visual with CategoryID from 'Products' and 'Total Sales', some categories show blank. What is the most likely cause?

Accepted Answer

There are ProductID values in Sales that do not exist in Products table.. When ProductID values in the Sales table do not have matching entries in the Products table, the relationship between the two tables will result in blank CategoryID values for those unmatched rows. In Power BI, a many-to-one relationship (the default) filters from the 'one' side (Products) to the 'many' side (Sales), but if a Sales row has a ProductID not present in Products, it cannot be matched, and any column from Products (like CategoryID) will appear as blank in visuals. This is a classic data integrity issue where the fact table contains orphaned foreign keys.

Answer

The 'Total Sales' measure is not properly referencing the Sales table.

Answer

The relationship between Sales and Products is set to many-to-one, single direction.

Answer

The relationship is set to both directions (bidirectional).

Question 3

You are reviewing a Power BI data source configuration in the data source settings. The exhibit shows the JSON representation of a data source. Which issue might arise from this configuration?

Accepted Answer

The authentication kind 'Key' is not supported for Azure SQL Database, causing connection failure.. Azure SQL Database does not support the 'Key' authentication kind in Power BI data source settings. Azure SQL Database requires either Windows authentication, database credentials (Username/Password), or Azure AD-based authentication (such as OAuth2 or Service Principal). The 'Key' authentication kind is typically used for Azure Storage or Cosmos DB, not for Azure SQL Database, so this configuration will cause a connection failure.

Answer

The server name contains a hyphen, which is invalid in SQL Server connection strings.

Answer

The CommandTimeout value is too low and may cause queries to time out.

Answer

The option 'CreateNavigationProperties' is set to false, which may prevent relationships from being created.

Question 4

You are connecting to an Azure SQL Database from Power BI Desktop. The database contains a view that returns thousands of rows. You only need the last 100 rows for analysis. What is the most efficient way to reduce the data loaded?

Accepted Answer

Use the 'Keep Top Rows' transformation in Power Query after applying a sort. It uses Power Query's 'Keep Top Rows' transformation after sorting the view by the desired order (e.g., descending on a date column). This approach pushes the sort and row-limiting logic to the source database via query folding, ensuring only the last 100 rows are transferred over the network, which is the most efficient method for reducing data loaded.

Answer

Write a native SQL query with a WHERE clause to limit rows

Answer

Use DirectQuery mode and add a filter in the report

Answer

Import all rows and then remove rows in Power Query

Question 5

You are designing a Power BI data model for a manufacturing company. Which TWO practices help optimize performance when using DirectQuery?

Accepted Answer

Reduce the number of columns in the fact query to only those needed. Reducing the number of columns in the fact query minimizes data transfer and improves DirectQuery performance. Option E is correct: Using a single date dimension table for all date columns simplifies relationships and reduces the number of joins required, enhancing query efficiency. Option A is wrong because disabling relationships would break the model integrity and force manual filtering, degrading performance. Option B is wrong because calculated columns in DirectQuery are pushed to the source, but they can still increase query complexity and resource usage; it is better to use native columns or measures. Option D is wrong because bidirectional cross-filtering can lead to ambiguous relationships and additional query overhead, harming performance.

Answer

Disable relationships between tables to reduce query complexity

Answer

Create calculated columns in Power Query instead of in DAX

Answer

Enable bidirectional cross-filtering for all relationships

Question 6

You are a data analyst for a multinational corporation. You are building a Power BI report that uses a large fact table (100 million rows) and several dimension tables. The data source is a SQL Server data warehouse. Users need to see near real-time data with a maximum latency of 15 minutes. The current import mode takes too long to refresh. You decide to use DirectQuery mode. However, queries are slow. You need to improve query performance. You consider creating aggregations in the data source. Which approach should you take in Power BI to leverage these aggregations?

Accepted Answer

Define aggregations in Power BI on the DirectQuery tables.. Power BI allows you to define aggregations on DirectQuery tables, which enables the engine to route queries to pre-aggregated data at the source (e.g., SQL Server indexed views or materialized views) when possible, significantly reducing query latency. This approach leverages the existing aggregations in the data source without changing the storage mode or importing data, maintaining near real-time freshness with a 15-minute latency requirement.

Answer

Create a composite model with an imported aggregated table.

Answer

Change the storage mode to Import for the fact table.

Answer

Create a SQL Server view that aggregates data and use it as the source.

Question 7

You have a Power BI report with a matrix visual showing sales by region and product category. You want to allow users to expand and collapse groups. Which feature should you enable?

Accepted Answer

Drill-down mode. Drill-down mode in a matrix visual allows users to expand and collapse hierarchical levels. When a hierarchy is present, enabling drill-down mode provides expand/collapse icons on row headers, letting users interactively show or hide subcategories. Option A (page tooltips) shows tooltip pages on hover, unrelated to expand/collapse. Option C (drill-through) navigates to another report page, not within the same visual. Option D (row and column subtotals) is a formatting feature for aggregating totals, not for expanding/collapsing groups.

Answer

Page tooltips

Answer

Drill-through

Answer

Row and column subtotals

Question 8

You are loading data from an Excel workbook that has multiple sheets. Each sheet contains sales data for a different region. You need to combine all sheets into one table. What is the most efficient approach?

Accepted Answer

Use 'Append Queries' for each sheet individually.. Using 'Append Queries' in Power Query allows you to combine multiple queries (one per sheet) into a single table. You can load all sheets as queries, then use the Append Queries feature to union them all at once, which is efficient and avoids manual repetition. Power Query's Append operation is designed for this purpose and is more efficient than loading separate tables into the model (C) or using Merge (B) which performs joins, not unions. 'From Folder' (D) is intended for combining multiple files, not sheets within a single workbook.

Answer

Use 'Merge Queries' to join all sheets into one.

Answer

Load each sheet as a separate table in the model and create a calculated table to union them.

Answer

Use Power Query's 'From Folder' option to combine all Excel files in a folder, then select 'Combine & Transform' to use the workbook as a sample.

Question 9

Your Power BI dataset uses DirectQuery to a SQL Server data warehouse. Users report that reports are slow. You need to improve performance without changing the data source. What should you do?

Accepted Answer

Create aggregated tables in Power BI using the Aggregations feature.. Creating aggregated tables in Power BI using the Aggregations feature allows you to pre-summarize data at a higher granularity while still using DirectQuery. This reduces the amount of data queried from the SQL Server data warehouse, improving report performance without changing the underlying data source or switching to Import mode.

Answer

Switch the dataset to Import mode.

Answer

Disable the 'Enable query reduction' option in Power BI Desktop.

Answer

Increase the memory limit of the on-premises data gateway.

Question 10

Which TWO actions are best practices for optimizing Power BI data models?

Accepted Answer

Replace text-based relationship columns with integer keys.. Replacing text-based relationship columns with integer keys (surrogate keys) reduces storage size and improves join performance. Power BI's VertiPaq engine compresses integer columns far more efficiently than text columns, leading to faster query execution and smaller memory footprint.

Answer

Use calculated columns instead of measures where possible.

Answer

Hide columns that are not used in reports.

Answer

Use many-to-many relationships instead of bridge tables.

Question 11

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 12

Refer to the exhibit. You are reviewing a DAX measure in Power BI. The measure is intended to calculate total sales for the year 2024. However, when used in a visual with a slicer on 'Sales[Date]', the measure does not respect the slicer selection. What is the most likely reason?

Accepted Answer

The FILTER function overrides the slicer filter context.. The FILTER function in the measure creates a new filter context that overrides the existing slicer filter context on 'Sales[Date]'. When CALCULATE evaluates the expression, it applies the FILTER as a table modifier, which replaces any external filters on the Date column, causing the slicer to be ignored. This is a common DAX behavior where explicit filter arguments in CALCULATE take precedence over existing filter contexts.

Answer

The CALCULATE function removes all filters by default.

Answer

The measure should use ALL(Sales[Date]) to respect slicers.

Answer

The DATE function syntax is incorrect.

Question 13

Your organization uses Power BI to analyze sales data stored in Azure SQL Database. The data model includes a fact table with millions of rows. To improve performance, you need to reduce the amount of data loaded into the model. Which action should you take?

Accepted Answer

Apply row-level filters in Power Query to import only relevant rows. Applying row-level filters in Power Query reduces the volume of data imported into the Power BI model by only loading rows that meet specific criteria. This directly minimizes the data footprint in memory, improving query and refresh performance, especially for fact tables with millions of rows stored in Azure SQL Database.

Answer

Use calculated tables in DAX to summarize data

Answer

Disable the Auto Date/Time feature

Answer

Configure incremental refresh with a date filter

Question 14

Which THREE of the following are best practices for data preparation in Power BI to improve performance and maintainability? (Select THREE.)

Accepted Answer

Filter out unnecessary rows as early as possible in the query. Filtering out unnecessary rows early in Power Query reduces the amount of data loaded into memory and processed in subsequent transformation steps. This practice, known as early filtering, minimizes the data footprint and improves both refresh performance and report responsiveness. By applying filters as the first transformation, you leverage query folding to push the filter logic to the source database, further enhancing efficiency.

Answer

Avoid renaming columns in Power Query; use original names

Answer

Keep all columns from the source to avoid missing data

Question 15

You are merging two queries in Power Query: 'Orders' and 'Customers'. The 'Orders' table has a 'CustomerID' column, and 'Customers' has 'CustomerID' and 'Name'. You need to bring the 'Name' into 'Orders' but only for matching CustomerIDs; unmatched rows should be removed. Which join kind should you use?

Accepted Answer

Inner. The Inner join kind in Power Query returns only rows where there is a match in both tables based on the key columns. Since the requirement is to bring the 'Name' into 'Orders' only for matching CustomerIDs and to remove unmatched rows, the Inner join is the correct choice. It ensures that only orders with a corresponding customer in the 'Customers' table are retained, and the 'Name' column is added to those matching rows.

Answer

Right Anti

Answer

Full Outer

Answer

Left Outer