PL-300 Practice Test 2 — 25 Questions

Question 1

You are a Power BI administrator for a large organization. A team has published a shared dataset to a Premium workspace. They use an XMLA endpoint to programmatically refresh the dataset daily. Recently, the refresh started failing with the error: 'The operation was canceled because the session was terminated by a concurrent operation.' The dataset is not partitioned. You need to ensure the refresh completes without errors. What should you do?

Accepted Answer

Enable the 'Refresh conflict detection' setting on the dataset to prevent concurrent operations.. The error 'The operation was canceled because the session was terminated by a concurrent operation' indicates that two refresh operations are conflicting on the same dataset. Enabling 'Refresh conflict detection' on the dataset prevents concurrent refreshes by queuing or blocking overlapping operations, ensuring the XMLA-triggered refresh completes without interruption.

Answer

Remove all scheduled refreshes and rely solely on the XMLA script.

Answer

Change the XMLA script to run less frequently, e.g., once per week.

Answer

Partition the dataset and refresh partitions sequentially.

Question 2

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.. Option A is correct because 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 3

You have developed a Power BI report that uses a live connection to an Azure Analysis Services (AAS) model. The AAS model is deployed in a different Azure region. Users report that the report loads slowly, sometimes taking over 30 seconds to render a single visual. You need to improve performance without changing the data model or the report structure. What should you do?

Accepted Answer

Deploy the Azure Analysis Services model to the same region as the Power BI workspace.. Option C is correct because deploying the Azure Analysis Services model to the same Azure region as the Power BI workspace minimizes network latency between the live connection client (Power BI) and the tabular model server. A live connection sends DAX queries over the XMLA protocol, and cross-region traffic introduces significant round-trip delays, which directly causes slow visual rendering. By co-locating the AAS server and the Power BI service in the same region, you reduce the physical distance and network hops, improving query response time without altering the model or report.

Answer

Enable the 'Reduce data shown in visuals' option in Power BI Desktop.

Answer

Implement row-level security (RLS) in the Azure Analysis Services model.

Answer

Convert the report to import mode and schedule a refresh.

Question 4

Drag and drop the steps to import data from a SQL Server database into Power BI Desktop into the correct order.

Accepted Answer

Open Power BI Desktop, then click Get Data and select SQL Server, then enter server name and database name and authentication, then select tables or write a SQL query and click Load or Transform.. Importing from SQL Server involves selecting the source, connecting to the server and database, choosing tables or queries, and loading or transforming data.

Answer

Click Get Data and select SQL Server, then open Power BI Desktop, then enter server name and database name and authentication, then select tables or write a SQL query and click Load or Transform.

Answer

Open Power BI Desktop, then enter server name and database name and authentication, then click Get Data and select SQL Server, then select tables or write a SQL query and click Load or Transform.

Answer

Open Power BI Desktop, then click Get Data and select SQL Server, then select tables or write a SQL query and click Load or Transform, then enter server name and database name and authentication.

Question 5

Your organization uses Power BI with large datasets from Azure Synapse Analytics. You need to reduce model size and improve query performance. You decide to use aggregations. Which type of aggregation table is most appropriate for pre-aggregating data at the year and category level?

Accepted Answer

Table-based aggregation. Option B is correct because table-based aggregation stores precomputed summaries in a separate table, which aligns with the requirement for pre-aggregating data at the year and category level. Option A (Calculated table) is incorrect because calculated tables are computed at refresh time and do not serve as pre-aggregated storage for query performance. Option C (Measure-based aggregation) is incorrect because measures are computed on the fly and not stored as separate tables, so they do not pre-aggregate data. Option D (In-memory aggregation) is not a standard aggregation type in Power BI.

Answer

Calculated table

Answer

Measure-based aggregation

Answer

In-memory aggregation

Question 6

You are building a Power BI report for a sales team. You have a table named 'Sales' with columns: SalesDate, ProductID, Quantity, UnitPrice, Discount. You also have a 'Date' table with continuous date range. You create a relationship from Sales[SalesDate] to Date[Date]. You need to calculate the total sales amount (Quantity * UnitPrice - Discount). You write the following measure:

TotalSales = SUMX(Sales, Sales[Quantity] * Sales[UnitPrice] - Sales[Discount])

The measure returns the correct total. However, when you slice by month from the Date table, the total does not change. What is the most likely cause?

Accepted Answer

The Date table is not marked as a date table, and the relationship is not set to filter in both directions.. Option C is correct because when a Date table is not marked as a date table, Power BI does not automatically recognize it as a time dimension. This prevents the relationship from properly propagating filters when using date hierarchies (e.g., month) from the Date table. Additionally, if the relationship is not set to filter in both directions, filters from the Date table may not flow to the Sales table, causing the measure to remain unchanged regardless of slicer selection. Marking the Date table as a date table and enabling bidirectional cross-filtering resolves this issue.

Answer

The Discount column might have negative values causing the total to be incorrect.

Answer

The measure should use SUM instead of SUMX because there are no row-level calculations.

Answer

The measure does not use the Date table; it references only the Sales table, so it ignores filters from other tables.

Question 7

You are examining a Power BI dataflow configuration. The dataflow is scheduled to refresh the 'Sales' entity daily and the 'Product' entity hourly. However, the 'Product' entity refresh fails every hour with an error indicating the SharePoint list data source is not accessible. You need to diagnose the issue. What is the most likely cause?

Accepted Answer

The refresh interval is too frequent for the incremental granularity of 'Day'. Option A is correct because the 'Product' entity is scheduled to refresh hourly, but if the dataflow has an incremental refresh policy set to a daily granularity (which is common to optimize performance), the hourly refresh tries to re-query the entire day's data each time. This excessive load on the SharePoint list can cause timeouts or errors that appear as 'data source not accessible'. The mismatch between the refresh frequency and the incremental granularity is the most likely cause, as the source cannot handle the repeated full scans.

Answer

Incremental refresh is not supported for SharePoint list data sources

Answer

The workspace ID is missing from the dataflow configuration

Answer

The on-premises data gateway is not configured for the SharePoint list

Question 8

Refer to the exhibit. You are reviewing a DAX measure for month-over-month sales growth. The measure returns BLANK for all months. What is the likely issue?

Accepted Answer

The FILTER function removes all context from the Date table, causing PriorSales to be calculated over the entire table.. Option A is correct because the FILTER function in the measure is likely used without proper context transition, causing it to iterate over the entire Date table and remove the current filter context. This results in PriorSales being calculated over all dates rather than the prior month, so the measure returns BLANK for every month when the IF condition compares the current sales (which may be blank due to context loss) against PriorSales.

Answer

The Date table is not marked as a date table.

Answer

The variable PriorDate returns a blank because MAX is used.

Answer

The IF condition incorrectly treats zero as blank.

Question 9

You are troubleshooting a Power BI DirectQuery model connected to Azure Synapse Analytics. The report shows stale data even though the underlying database is updated hourly. What should you check first?

Accepted Answer

Whether the report has 'Disable caching' enabled in the dataset settings.. Option C is correct. In a DirectQuery model, data is not stored in Power BI; each query goes to the source. However, Power BI may cache query results at the report level, which can cause stale data. The 'Disable caching' option, when enabled, forces fresh queries to the source, ensuring up-to-date data. Option A is incorrect because Import mode is not used here; DirectQuery mode is specified. Option B is incorrect because RLS permissions affect data visibility, not freshness. Option D is incorrect because scheduled refresh is only applicable to Import models, not DirectQuery.

Answer

Whether the dataset is using Import mode instead of DirectQuery.

Answer

Whether the user has RLS permissions that filter data incorrectly.

Answer

Whether the dataset is configured for scheduled refresh.

Question 10

You run the above DAX query in DAX Studio. The result set shows a row for each Category and Year combination, but the Total Sales and Total Cost columns are both blank. What is the most likely reason?

Accepted Answer

There is no active relationship between the Sales table and the Product and Date tables. SUMMARIZECOLUMNS automatically adds filter context based on the columns used. If there is no active relationship between the Sales table and the Product or Date tables, the filter context from Category and Year cannot propagate to Sales, resulting in blank aggregates. Option D is correct. Option A is incorrect because if the Sales[Amount] column contained only BLANK values, only Total Sales would be blank, but here both Total Sales and Total Cost are blank, indicating a broader relationship issue. Option B is incorrect because SUMMARIZECOLUMNS can compute multiple aggregate columns. Option C is incorrect because the ORDER BY clause does not affect aggregation; it only sorts results after aggregation.

Answer

The Sales[Amount] column contains only BLANK values

Answer

SUMMARIZECOLUMNS cannot compute two aggregate columns

Answer

The ORDER BY clause is causing the aggregation to fail

Question 11

A Power BI administrator reviews the JSON configuration for a dataset named SalesDataset. The dataset is deployed to a Premium capacity workspace. The data source is an on-premises SQL Server. The administrator notices that the dataset has never refreshed successfully. Based on the exhibit, what is the most likely cause of the refresh failure?

Accepted Answer

The dataset's defaultMode is set to Push, which does not support scheduled refresh. Option C is correct because when a dataset's defaultMode is set to 'Push', it is designed to receive data only via the Push API and does not support scheduled refresh. Since the dataset has never refreshed successfully and the JSON configuration shows defaultMode as Push, the scheduled refresh will always fail regardless of the gateway or data source configuration.

Answer

The refresh schedule specifies a frequency of Weekly, but the time is in UTC and not adjusted for the local time zone

Answer

The dataset uses Integrated Security in the connection string, which is not supported for scheduled refresh

Answer

The dataset is in a Premium capacity workspace, which does not support scheduled refresh for on-premises data sources

Question 12

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 13

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 14

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 15

Match each Power BI concept to its definition.

Accepted Answer

Star Schema: A data model structure where fact tables are connected to dimension tables in a star-like pattern.. Star schema uses denormalized dimensions, snowflake schema normalizes dimensions further. Calculated columns are static row-by-row evaluations; measures are dynamic aggregations based on filter context.

Answer

Star Schema: A normalized schema where dimension tables are split into sub-dimensions.

Answer

Snowflake Schema: A denormalized schema where fact table connects directly to dimension tables.

Question 16

Match each DAX function category to an example function.

Accepted Answer

Aggregation: SUM. Correct matches: Aggregation → SUM, Logical → IF, Filter → CALCULATE. Common confusions: confusing text functions (LEFT) with date/time (DATE) and vice versa.

Answer

Text: DATE

Answer

Date/Time: LEFT

Question 17

Match each Power BI license type to its description.

Accepted Answer

Power BI Free: Allows users to create reports and dashboards for personal use only. Cannot share with others.. Power BI Free is for personal use only, Power BI Pro enables sharing and collaboration, Power BI Premium Per User adds advanced features per user, and Power BI Premium provides dedicated capacity. Common confusions include mixing the sharing capabilities of Pro with Premium Per User and the personal limitation of Free with Premium.

Answer

Power BI Premium Per User: Enables collaboration, sharing, and publishing content with other Pro users.

Answer

Power BI Premium: Allows users to create reports and dashboards for personal use only.

Question 18

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 19

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.. Option D is correct because 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 20

You are connecting to a SQL Server database using Import mode. The source table contains a column 'SalesAmount' with a few null values. You need to replace nulls with 0 before loading. What is the most efficient step to achieve this in Power Query Editor?

Accepted Answer

Use 'Replace Values' to replace null with 0. Option A is correct because 'Replace Values' in Power Query Editor is the most efficient way to replace null values in a column with 0. It directly transforms the column in a single step without requiring additional logic or table scans, and it generates a clean M code step (Table.ReplaceValue) that operates natively on the column's nulls.

Answer

Use 'Replace Errors' with value 0

Answer

Use 'Fill Down' to propagate previous values

Answer

Add a custom column with an if statement