PL-300 Practice Test 2 — 25 Questions

Question 1

You are designing a Power BI report for a sales team. The team needs to see revenue by product category, but also want to view daily trends for a selected product. The data has over 10 million rows. What visual design approach minimizes report load time?

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

Accepted Answer

Create a drillthrough page with a line chart showing daily revenue, and use category page as source. Option D is correct because a drillthrough page keeps the main category page lightweight and only loads the daily revenue line chart when a user right-clicks a product and drills through, so the 10 million-row detail query runs on demand rather than on every page render. This design also lets the drillthrough page be filtered to the selected product, reducing the data volume processed by the line chart. Options A and C are wrong because rendering both category and daily-trend visuals on one page forces all queries, including the high-cardinality daily aggregation, to execute on initial load. Option B is wrong because bookmarks only toggle visual visibility on the same page; hidden visuals and their underlying queries can still be evaluated, so it does not reliably reduce load time.

Answer

Use a custom visual that combines both views in one chart

Answer

Use bookmarks to switch between category view and daily trend view

Answer

Place a stacked column chart showing all categories and a line chart for trend on the same page

Question 2

You are a data analyst at an online retailer. You import a CSV file containing product reviews into Power BI Desktop. The file has a column named ReviewDate that currently loads as the Text data type, with values formatted like '2024-07-15T09:30:00Z'. You need to change this column to the Date/Time/Timezone data type, but when you select that type in Power Query, the transformation fails for many rows. You need to resolve the failure while preserving the original timestamp data. What should you do?

Accepted Answer

Replace the trailing 'Z' with '+00:00' in the column, then change the data type to Date/Time/Timezone.. The Date/Time/Timezone type in Power Query requires an explicit numeric offset such as +00:00, not the ISO 8601 Z shorthand. Replacing Z with +00:00 preserves the UTC instant and lets the conversion succeed. The other approaches either misinterpret the format, discard required time data, or produce a timezone-less result.

Answer

Add a custom column that uses DateTime.FromText on the original values and then delete the original column.

Answer

Change the column to the Date data type instead, which discards the time and timezone portions and avoids the error.

Answer

Use the Locale option in the Change Type dialog and select English (United States) before applying the Date/Time/Timezone type.

Question 3

You are a Power BI data analyst for a subscription software company. You import a table named Subscriptions from an OData feed. The table contains a column named BillingPeriod that stores values such as 'Monthly', 'Annual', and 'Quarterly'. A report author needs a numeric column that converts each value to the number of months in the billing period (1, 12, and 3 respectively) so that revenue can be normalized. You must add this column in Power Query without changing the source system. What should you do?

Accepted Answer

Add a conditional column that maps each text value to its corresponding number of months, then change the new column's data type to Whole Number.. A conditional column in Power Query explicitly maps each billing period label to its numeric month count, which is deterministic and easy to audit. Setting the new column to Whole Number makes it usable for arithmetic in the model. The other options either rely on fragile inference, fail outright on non-numeric text, or place the logic in the wrong layer.

Answer

Use the Column From Examples feature, entering '1' next to 'Monthly' and letting Power BI infer the remaining mappings.

Answer

Create a DAX calculated column in the semantic model that uses SWITCH to translate each billing period into months.

Answer

Change the data type of the BillingPeriod column to Whole Number and rely on Power Query's automatic value conversion.

Question 4

You are building a Power BI semantic model that includes a Customers table and a Sales table. The Customers table has a unique CustomerID column. The Sales table has a CustomerID column that references the Customers table. You need to create a relationship between the two tables. Which type of relationship should you create?

Accepted Answer

One-to-many relationship with Customers as the one side and Sales as the many side.. The correct relationship is one-to-many from Customers to Sales because each customer is unique in the Customers table and can have multiple related rows in the Sales table. This is the standard dimension-to-fact relationship in a star schema, enabling efficient filtering and aggregation.

Answer

Many-to-many relationship between Customers and Sales.

Answer

One-to-one relationship between Customers and Sales.

Answer

Many-to-one relationship with Sales as the one side and Customers as the many side.

Question 5

You are modeling data for a subscription business in Power BI Desktop. The Subscriptions table has StartDate and EndDate columns, and the Dates table is marked as the official date table. Analysts need a measure that counts subscriptions that were active on any given day selected in a slicer from Dates, and the relationship between Subscriptions and Dates must remain inactive to avoid ambiguity. Which approach should you use?

Accepted Answer

Create a measure that uses FILTER over the Subscriptions table comparing StartDate and EndDate to the selected date range, evaluated inside CALCULATE.. Counting subscriptions active on a selected date requires an interval test across two date columns, which no single relationship can express. Iterating the fact table with FILTER and comparing both StartDate and EndDate to the slicer context captures the overlap precisely. USERELATIONSHIP handles only one relationship, calculated columns cannot react to slicer selections, and cross-filter direction does not perform interval logic.

Answer

Change the relationship between Subscriptions and Dates to bidirectional cross-filtering and count the Subscriptions rows.

Answer

Create a measure that uses CALCULATE with USERELATIONSHIP to activate the relationship between Subscriptions and Dates inside the measure.

Answer

Create a calculated column on Subscriptions that flags active rows, then use COUNTROWS on the filtered Subscriptions table in the measure.

Question 6

You are creating a Power BI report and need to add a visual that allows users to dynamically change the measure displayed in a chart. Which feature should you use?

Accepted Answer

Field parameters. Field parameters provide a way to let report users choose which measures or dimensions appear in a visual. By adding a field parameter to a slicer, users can select from a list of measures, and the visual updates accordingly. This is the most efficient method to achieve dynamic measure switching without creating multiple visuals or bookmarks.

Answer

Bookmarks

Answer

What-if parameters

Answer

Calculation groups

Question 7

Which TWO actions can improve performance of a Power BI DirectQuery model?

Accepted Answer

Ensure proper indexing in the source database. Proper indexing in the source database reduces the query execution time for DirectQuery models. DirectQuery sends queries to the source database in real-time, so efficient indexes on columns used in filters, joins, and aggregations minimize table scans and improve retrieval speed.

Answer

Switch the model to Import mode

Answer

Enable bidirectional cross-filtering on all relationships

Answer

Use calculated columns with complex logic

Question 8

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. `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 9

Which THREE of the following are best practices when designing Power BI reports for mobile devices? (Select three.)

Accepted Answer

Create a dedicated mobile layout view. Option A is correct because Power BI Desktop provides a dedicated Mobile Layout view (View > Mobile Layout) that lets you rearrange and resize visuals specifically for phone portrait orientation without affecting the desktop canvas. Option B is correct because small phone screens and varied lighting conditions make large font sizes and high-contrast colors essential for legibility and accessibility on mobile devices. Option D is correct because limiting each page to roughly 3-5 visuals keeps the mobile layout scannable and avoids excessive vertical scrolling and slow rendering on phones. Option C is not a mobile best practice per se: custom visuals are chosen for analytical capability, not for mobile optimization, and some custom visuals render poorly or are not optimized for small screens. Option E is not recommended because stacking multiple slicers consumes scarce screen space and complicates touch interaction; mobile designs typically favor a single, well-chosen slicer or filter pane instead.

Answer

Use custom visuals for advanced analytics

Answer

Include multiple slicers for flexible filtering

Question 10

You are designing a star schema for a sales analysis report. The source data includes Order Details, Products, Customers, and Dates. Which table should be the fact table?

Accepted Answer

Order Details. In a star schema, the fact table stores quantitative, measurable data (metrics) and foreign keys linking to dimension tables. Order Details contains sales transactions with measures like quantity and revenue, making it the correct fact table for sales analysis.

Answer

Dates

Answer

Customers

Answer

Products

Question 11

You have a table with columns 'Product', 'Category', and 'Sales'. You want to create a hierarchy that allows users to drill down from Category to Product. Which is the correct order to create the hierarchy?

Accepted Answer

Category -> Product. In Power BI, a hierarchy is built from the highest (most aggregated) level to the lowest (most granular) level. To allow drill-down from Category to Product, Category must be the top level and Product the child level. Option C correctly orders Category → Product, enabling users to expand from category-level totals to individual product sales.

Answer

Product -> Category -> Sales

Answer

Product -> Category

Answer

Sales -> Product -> Category

Question 12

You have a Power BI data model with a table 'Orders' that has columns: 'OrderID', 'OrderDate', 'CustomerName', 'Region', 'Product', 'Quantity', 'UnitPrice'. You want to create a measure that calculates total sales amount. Which DAX expression should you use?

Accepted Answer

Total Sales = SUMX(Orders, Orders[Quantity] * Orders[UnitPrice]). SUMX is an iterator function that evaluates the expression `Orders[Quantity] * Orders[UnitPrice]` for each row in the Orders table and then sums the results. This is necessary because DAX does not support direct multiplication of two columns inside SUM; SUM expects a single column reference, not an expression. SUMX performs row-by-row evaluation, which correctly computes the total sales amount as the sum of (Quantity × UnitPrice) across all orders.

Answer

Total Sales = COUNTROWS(Orders)

Answer

Total Sales = AVERAGE(Orders[Quantity]) * AVERAGE(Orders[UnitPrice])

Answer

Total Sales = SUM(Orders[Quantity] * Orders[UnitPrice])

Question 13

You are the Power BI administrator for a company that uses Microsoft 365. The security team requires that when a user opens a Power BI report on a personal device, the user must authenticate with Microsoft Entra ID and satisfy a conditional access policy that demands multifactor authentication. The report is in a workspace that is not backed by Fabric capacity. Which feature should you enable to meet this requirement?

Accepted Answer

Microsoft Entra ID Conditional Access. The requirement is to force MFA when users open a report on personal devices. Because Power BI authenticates users through Microsoft Entra ID, a Conditional Access policy that targets the Power BI app and requires MFA will enforce the challenge at sign-in. This works regardless of whether the workspace uses Fabric capacity. Other features like sensitivity labels, RLS, or Embedded do not enforce interactive MFA.

Answer

Power BI Embedded

Answer

Row-level security (RLS)

Answer

Sensitivity labels

Question 14

You have a Power BI model with a table 'Sales' and a related 'Product' table. You want to count the number of distinct products sold. Which DAX expression should you use?

Accepted Answer

DISTINCTCOUNT(Sales[ProductID]). DISTINCTCOUNT(Sales[ProductID]) returns the number of unique ProductID values in the Sales table, which directly answers the requirement to count distinct products sold. This function counts each distinct value in the specified column, ignoring duplicates, and is the standard DAX measure for distinct count calculations.

Answer

COUNTROWS(Sales)

Answer

COUNT(Sales[ProductID])

Answer

COUNTA(Sales[ProductID])

Question 15

You are importing data from a CSV file that contains a column 'OrderDate' with dates in the format 'MM/dd/yyyy'. Some rows have invalid dates like '02/30/2023'. What is the best way to handle these errors in Power Query?

Accepted Answer

Use 'Replace Errors' to replace error values with null.. 'Replace Errors' in Power Query allows you to replace error values (which occur when Power Query fails to convert an invalid date like '02/30/2023' to the Date type) with null. This preserves the rest of the data and keeps the query running without interruption, while clearly marking invalid entries for later handling or analysis.

Answer

Remove rows with errors using 'Remove Rows' > 'Remove Errors'.

Answer

Change the data type to 'Date' and ignore errors.

Answer

Filter the column to exclude rows where the date is invalid after type conversion.

Question 16

Which TWO data sources can be used with DirectQuery mode in Power BI? (Choose two.)

Accepted Answer

SQL Server. DirectQuery mode in Power BI requires a data source that supports query pass-through to a backend engine, and SQL Server (option B) qualifies because Power BI issues native T-SQL queries against the relational database in real time without importing data. Azure SQL Database (option C) is likewise a supported DirectQuery source, since it is a cloud-based SQL Server engine that accepts the same T-SQL query folding and live connection pattern. In contrast, Excel workbook (A), CSV file (D), and SharePoint list (E) are file- or list-based sources that Power BI imports rather than querying live, so they are not valid DirectQuery data sources.

Answer

Excel workbook

Answer

CSV file

Answer

SharePoint list

Question 17

You are a Power BI developer at a healthcare organization. You are building a report that must comply with HIPAA regulations. You need to ensure that patient data is not exposed to unauthorized users. You plan to use Row-Level Security (RLS) with roles defined in Power BI Desktop. However, you also need to limit the data imported into the model to only necessary columns. The source is an Azure SQL Database with a table 'Patients' containing columns: PatientID, Name, SSN, Diagnosis, AdmissionDate, DischargeDate. Which two actions should you take? (Choose TWO)

Accepted Answer

Create RLS roles to restrict access by Diagnosis.. Option A is correct because defining RLS roles in Power BI Desktop and mapping them to users in the Power BI service enforces row-level filtering so that each user only sees the patient rows they are authorized to view, which is a core HIPAA minimum-necessary access control. Option E is correct because removing SSN and Name in Power Query before loading implements data minimization, ensuring sensitive identifiers are never imported into the semantic model where they could be exposed. Option B is not correct because storing credentials in the Power BI service is a connectivity/authentication practice, not a data-exposure control for this scenario. Option C is not correct because disabling query caching does not restrict which data is imported or who can see it. Option D is not correct because an encrypted connection protects data in transit but does not limit imported columns or enforce row-level access for report consumers.

Answer

Store data source credentials in the Power BI service.

Answer

Disable query caching for the dataset.

Answer

Use encrypted connection to the database.

Question 18

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 19

You are merging two queries in Power Query. Query 'Orders' contains columns: OrderID, CustomerID, OrderDate. Query 'Customers' contains columns: CustomerID, CustomerName, Segment. You need to add the CustomerName to the Orders query. The relationship between Orders and Customers is many-to-one. Which join kind should you use?

Accepted Answer

Left Outer. The goal is to retain all rows from the Orders table while adding CustomerName from the Customers table. A Left Outer join returns all rows from the first (left) table and only matching rows from the second (right) table, filling non-matches with null. Since the relationship is many-to-one, each OrderID may have a matching CustomerID, and you want to keep every order even if a customer is missing — exactly what Left Outer does.

Answer

Inner

Answer

Right Outer

Answer

Full Outer

Question 20

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