Sample questions
Microsoft Power BI Data Analyst PL-300 practice questions
You are developing a Power BI report to analyze sales performance. The data model includes a 'Sales' fact table with a 'Date' column and a 'Region' dimension table. You need to create a measure that calculates the total sales amount for the current year compared to the previous year. Which TWO of the following steps are required to implement this calculation correctly?
Trap 1: Use the Quick Measure feature to create a 'Year-over-year change'…
Quick measures are optional, not required.
Trap 2: Apply the CALCULATE function to switch between years.
CALCULATE modifies filter context but is not specific to year comparison.
Trap 3: Ensure the 'Sales' table has a relationship to the 'Date' table…
Should be many-to-one, not many-to-many.
- A
Use the Quick Measure feature to create a 'Year-over-year change' measure.
Why wrong: Quick measures are optional, not required.
- B
Create a separate date table and mark it as a date table in Power BI.
Required for time intelligence functions.
- C
Apply the CALCULATE function to switch between years.
Why wrong: CALCULATE modifies filter context but is not specific to year comparison.
- D
Use the SAMEPERIODLASTYEAR function in a DAX measure.
Standard function for previous year comparison.
- E
Ensure the 'Sales' table has a relationship to the 'Date' table with a many-to-many cardinality.
Why wrong: Should be many-to-one, not many-to-many.
A company has a Power BI dataset that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, ShipDate, and Amount. They want to create a measure that calculates the number of orders shipped within 3 days of the order date. Which THREE of the following steps are necessary to create this measure?
Trap 1: Use COUNTROWS without any filter.
COUNTROWS without filter counts all orders, not just those shipped within 3 days.
Trap 2: Use SUM to add up the Amount column.
SUM adds values, not counts; we need to count rows.
- A
Use FILTER to filter the Orders table based on the condition.
FILTER is required to restrict rows to those shipped within 3 days.
- B
Use COUNTROWS without any filter.
Why wrong: COUNTROWS without filter counts all orders, not just those shipped within 3 days.
- C
Use SUM to add up the Amount column.
Why wrong: SUM adds values, not counts; we need to count rows.
- D
Use COUNTROWS inside CALCULATE.
CALCULATE with COUNTROWS and a filter condition counts the filtered rows.
- E
Use DATEDIFF to calculate the difference between ShipDate and OrderDate.
DATEDIFF is used to calculate the date difference in days.
A company has a Power BI report that uses a DirectQuery dataset from an Azure SQL Database. Users report that the report is slow when filtering by date. Which action should you take to improve performance?
Trap 1: Increase the date range filter to include more data
Increasing data range exacerbates performance issues.
Trap 2: Disable cross-filtering in the report
Cross-filtering doesn't impact DirectQuery performance directly.
Trap 3: Remove unnecessary columns from the date table
Reducing columns may help but not primarily for date filtering performance.
- A
Create a separate date dimension table and relate it to the fact table
A date dimension improves query performance and enables time intelligence.
- B
Increase the date range filter to include more data
Why wrong: Increasing data range exacerbates performance issues.
- C
Disable cross-filtering in the report
Why wrong: Cross-filtering doesn't impact DirectQuery performance directly.
- D
Remove unnecessary columns from the date table
Why wrong: Reducing columns may help but not primarily for date filtering performance.
A Power BI report contains a table visual that displays employee names and their total sales. The data model includes an Employee table with columns: EmployeeID, Name, Department, and HireDate. The Sales table has columns: SaleID, EmployeeID, Amount, and SaleDate. The relationship between Employee and Sales is one-to-many. The user wants to see only employees who have made at least one sale. However, the table shows all employees, including those with no sales (blank Amount). What is the most likely reason?
Trap 1: The EmployeeID column in the Employee table is hidden.
Hiding a column does not affect the display of names or the filtering behavior.
Trap 2: The relationship is many-to-one, not one-to-many.
The scenario states one-to-many, which is correct; many-to-one would be the inverse.
Trap 3: The relationship direction is set to Single from Employee to Sales.
A single-direction relationship from Employee to Sales is appropriate and does not cause employees with no sales to appear.
- A
The EmployeeID column in the Employee table is hidden.
Why wrong: Hiding a column does not affect the display of names or the filtering behavior.
- B
The relationship is many-to-one, not one-to-many.
Why wrong: The scenario states one-to-many, which is correct; many-to-one would be the inverse.
- C
The relationship direction is set to Single from Employee to Sales.
Why wrong: A single-direction relationship from Employee to Sales is appropriate and does not cause employees with no sales to appear.
- D
There is no visual-level filter to exclude blank values.
To show only employees with sales, a visual-level filter should be applied on the Amount field to exclude blanks.
A data analyst creates a Power BI report that uses a date table with a continuous date range. They want to calculate the running total of sales over the last 12 months, ending on the last date in the current filter context. Which DAX expression should they use?
Trap 1: CALCULATE(SUM(Sales[Amount]), DATESINPERIOD('Date'[Date],…
DATESINPERIOD is actually the correct function, but it is not listed as an option; option D is fictional. The correct answer is B as it is the only feasible one.
Trap 2: TOTALMTD(SUM(Sales[Amount]), 'Date'[Date])
TOTALMTD calculates month-to-date, not a 12-month running total.
Trap 3: CALCULATE(SUM(Sales[Amount]), DATESYTD('Date'[Date]))
DATESYTD returns year-to-date, not a rolling 12-month period.
- A
CALCULATE(SUM(Sales[Amount]), DATESBETWEEN('Date'[Date], MAX('Date'[Date]) - 365, MAX('Date'[Date])))
DATESBETWEEN with MAX date minus 365 days approximates the last 12 months, but this may not account for leap years; however, among the options, this is the most appropriate for a running 12-month total. A more precise method would use DATESINPERIOD, but that is not listed.
- B
CALCULATE(SUM(Sales[Amount]), DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -12, MONTH))
Why wrong: DATESINPERIOD is actually the correct function, but it is not listed as an option; option D is fictional. The correct answer is B as it is the only feasible one.
- C
TOTALMTD(SUM(Sales[Amount]), 'Date'[Date])
Why wrong: TOTALMTD calculates month-to-date, not a 12-month running total.
- D
CALCULATE(SUM(Sales[Amount]), DATESYTD('Date'[Date]))
Why wrong: DATESYTD returns year-to-date, not a rolling 12-month period.
Which TWO of the following are valid ways to create a measure in Power BI?
Trap 1: From the Format pane, add a measure.
The Format pane is for visual formatting.
Trap 2: From Power Query Editor, add a custom column.
Power Query is for data transformation, not measures.
Trap 3: From the Visualizations pane, click New Measure.
The Visualizations pane does not have this option.
- A
From the Modeling tab, click New Measure.
This is the standard way to create a measure.
- B
Right-click a table in the Fields pane and select New Measure.
This is another valid method.
- C
From the Format pane, add a measure.
Why wrong: The Format pane is for visual formatting.
- D
From Power Query Editor, add a custom column.
Why wrong: Power Query is for data transformation, not measures.
- E
From the Visualizations pane, click New Measure.
Why wrong: The Visualizations pane does not have this option.
A user reports that a Power BI report is not refreshing data from a SQL Server database. The dataset uses Import mode. The gateway cluster shows all gateways are online. What is the most likely cause?
Trap 1: The report is using a scheduled refresh with a conflicting time.
Scheduled refresh conflicts may cause delays but not outright failure with no error.
Trap 2: The gateway version is incompatible with the SQL Server version.
Gateway version incompatibility is rare and usually causes a different error.
Trap 3: The dataset uses DirectQuery mode which requires a live connection.
The dataset uses Import mode, not DirectQuery.
- A
The report is using a scheduled refresh with a conflicting time.
Why wrong: Scheduled refresh conflicts may cause delays but not outright failure with no error.
- B
The gateway version is incompatible with the SQL Server version.
Why wrong: Gateway version incompatibility is rare and usually causes a different error.
- C
The dataset uses DirectQuery mode which requires a live connection.
Why wrong: The dataset uses Import mode, not DirectQuery.
- D
The data source credentials are incorrect or expired.
Correct. Expired or incorrect credentials are a common cause of refresh failures.
You need to deploy a Power BI report from a development workspace to a production workspace. You want to ensure that the report uses the production dataset connection string without manual changes. What should you use?
Trap 1: Manually update the data source in the production workspace after…
Manual updates are error-prone and not automated.
Trap 2: Use a Power BI template (.pbit) and change the connection string…
This still requires manual change per deployment.
Trap 3: Publish the report directly to the production workspace and update…
No automation for connection string.
- A
Manually update the data source in the production workspace after deployment.
Why wrong: Manual updates are error-prone and not automated.
- B
Use a Power BI template (.pbit) and change the connection string before publishing.
Why wrong: This still requires manual change per deployment.
- C
Configure a deployment pipeline with parameter rules to override the data source.
Pipeline rules can automatically set production parameters.
- D
Publish the report directly to the production workspace and update the dataset.
Why wrong: No automation for connection string.
You manage a Power BI deployment that uses deployment pipelines. After promoting content from Development to Test, you notice that the Test workspace dataset uses a different data source than expected. What is the most likely reason?
Trap 1: The pipeline didn't deploy the dataset because it was already in…
The pipeline deploys all content, including datasets.
Trap 2: The data source credentials were not applied during deployment.
Credentials are separate; the data source itself is what's mismatched.
Trap 3: The Test workspace has a separate dataset that was manually created.
The pipeline overwrites the dataset in the target workspace.
- A
The pipeline didn't deploy the dataset because it was already in Test.
Why wrong: The pipeline deploys all content, including datasets.
- B
The data source credentials were not applied during deployment.
Why wrong: Credentials are separate; the data source itself is what's mismatched.
- C
The dataset parameters were not configured in the deployment pipeline rules.
Parameter rules are required to update data source connections across stages.
- D
The Test workspace has a separate dataset that was manually created.
Why wrong: The pipeline overwrites the dataset in the target workspace.
You are deploying a Power BI solution to a customer. The customer requires that all report access be controlled via Azure Active Directory (Azure AD) groups. You have a single workspace with multiple reports. What is the best practice for managing permissions?
Trap 1: Create a Power BI group and add users to it.
Power BI groups are deprecated; use Azure AD groups.
Trap 2: Assign each user directly to the workspace role.
Not scalable; Azure AD groups are better.
Trap 3: Share each report individually with users.
Does not use workspace permissions.
- A
Create a Power BI group and add users to it.
Why wrong: Power BI groups are deprecated; use Azure AD groups.
- B
Assign each user directly to the workspace role.
Why wrong: Not scalable; Azure AD groups are better.
- C
Share each report individually with users.
Why wrong: Does not use workspace permissions.
- D
Add an Azure AD group to the workspace role.
This is the recommended approach for scalable access.
You manage a Power BI workspace that contains a dataset refreshed daily from an on-premises SQL Server. Users report that the report shows data from two days ago. You verify that the scheduled refresh ran successfully this morning. What is the most likely cause?
Trap 1: The refresh took longer than expected and timed out.
The refresh completed successfully, so timeout is not the issue.
Trap 2: The scheduled refresh is not set to refresh the dataset.
The refresh ran successfully, so scheduling is not the issue.
Trap 3: The on-premises data gateway is offline.
If the gateway were offline, the refresh would fail.
- A
The gateway is using a cached version of the data due to a misconfigured data source.
A misconfigured gateway cache can cause stale data.
- B
The refresh took longer than expected and timed out.
Why wrong: The refresh completed successfully, so timeout is not the issue.
- C
The scheduled refresh is not set to refresh the dataset.
Why wrong: The refresh ran successfully, so scheduling is not the issue.
- D
The on-premises data gateway is offline.
Why wrong: If the gateway were offline, the refresh would fail.
Which TWO actions should you take to ensure that a Power BI report deployed to production is available to users even if the gateway is offline for maintenance?
Trap 1: Create a Power BI Premium capacity to ensure high availability.
Premium capacity does not bypass gateway dependency.
Trap 2: Schedule the dataset refresh to run during the maintenance window.
This would fail if the gateway is offline.
Trap 3: Use DirectQuery instead of Import mode to avoid gateway dependency.
DirectQuery still requires gateway for on-premises sources.
- A
Create a Power BI Premium capacity to ensure high availability.
Why wrong: Premium capacity does not bypass gateway dependency.
- B
Schedule the dataset refresh to run during the maintenance window.
Why wrong: This would fail if the gateway is offline.
- C
Use DirectQuery instead of Import mode to avoid gateway dependency.
Why wrong: DirectQuery still requires gateway for on-premises sources.
- D
Create a separate dataset in the cloud that caches the data.
A cloud dataset can be refreshed when the gateway is online.
- E
Implement a disaster recovery plan that includes a secondary gateway.
A secondary gateway can take over during maintenance.
Which THREE steps should you perform to deploy a Power BI solution from development to production using deployment pipelines?
Trap 1: Create a new workspace manually in production.
Pipelines create workspaces automatically.
Trap 2: Assign Power BI Pro licenses to all developers.
Licenses are prerequisite, not part of deployment steps.
- A
Create a new workspace manually in production.
Why wrong: Pipelines create workspaces automatically.
- B
Set up deployment pipeline rules to modify parameters (e.g., database name).
Rules automate configuration changes.
- C
Assign Power BI Pro licenses to all developers.
Why wrong: Licenses are prerequisite, not part of deployment steps.
- D
Deploy content from development to test, then to production.
Sequential deployment is the pipeline workflow.
- E
Create a development workspace and add content.
Content starts in development.
Your Power BI dataset uses DirectQuery to an Azure SQL Database. Users complain that the report is slow. You need to improve query performance without changing the data source. What should you do?
Trap 1: Add more visuals to the report to distribute the load.
More visuals send more queries.
Trap 2: Switch the dataset to Import mode.
This changes the data source mode, not DirectQuery.
Trap 3: Increase the scheduled refresh frequency.
Refresh frequency does not affect DirectQuery performance.
- A
Reduce the number of columns and rows retrieved by the report visuals.
Less data means faster queries.
- B
Add more visuals to the report to distribute the load.
Why wrong: More visuals send more queries.
- C
Switch the dataset to Import mode.
Why wrong: This changes the data source mode, not DirectQuery.
- D
Increase the scheduled refresh frequency.
Why wrong: Refresh frequency does not affect DirectQuery performance.
You deploy a Power BI app to a workspace with an app-only license (Premium Per User). Users report that they can access the app but cannot see any visuals in the reports. The dataset uses Import mode. What is the most likely issue?
Trap 1: The report uses DirectQuery and the data source is offline.
DirectQuery would show an error, not blank visuals.
Trap 2: The report is published to a shared dataset that has been deleted.
A deleted dataset would show an error message.
Trap 3: The dataset has row-level security (RLS) that filters all rows for…
RLS would show visuals with no data, not missing visuals.
- A
The report uses DirectQuery and the data source is offline.
Why wrong: DirectQuery would show an error, not blank visuals.
- B
The users do not have a Premium Per User license assigned.
PPU content requires PPU license to render.
- C
The report is published to a shared dataset that has been deleted.
Why wrong: A deleted dataset would show an error message.
- D
The dataset has row-level security (RLS) that filters all rows for these users.
Why wrong: RLS would show visuals with no data, not missing visuals.
Which THREE factors should you consider when planning the deployment of Power BI content to a large enterprise with multiple regions?
Trap 1: The number of visuals per report page.
This is a report design concern, not deployment infrastructure.
Trap 2: The currency format used in reports for each region.
Formatting is a report design consideration, not deployment.
- A
Data residency requirements for each region.
Data must stay within geographic boundaries due to compliance.
- B
The number of visuals per report page.
Why wrong: This is a report design concern, not deployment infrastructure.
- C
The currency format used in reports for each region.
Why wrong: Formatting is a report design consideration, not deployment.
- D
The use of deployment pipelines to promote content between regions.
Pipelines help manage content lifecycle across environments.
- E
The location and performance of on-premises data gateways.
Gateways should be close to data sources for optimal refresh.
You review the dataset refresh history. The second refresh took 30 minutes and failed. What is the most likely reason for the failure?
Exhibit
Refer to the exhibit. Dataset Refresh History: Refresh #1: Start: 2024-01-15 01:00:00, End: 2024-01-15 01:05:00, Status: Completed Refresh #2: Start: 2024-01-15 02:00:00, End: 2024-01-15 02:30:00, Status: Failed Refresh #3: Start: 2024-01-15 03:00:00, End: 2024-01-15 03:03:00, Status: Completed
Trap 1: The refresh schedule conflicted with another refresh.
No other refresh was running at 2:00 AM.
Trap 2: The on-premises data gateway was offline.
Other refreshes succeeded, so gateway was online.
Trap 3: The data source was unavailable.
Other refreshes succeeded, so data source was available.
- A
The refresh schedule conflicted with another refresh.
Why wrong: No other refresh was running at 2:00 AM.
- B
The on-premises data gateway was offline.
Why wrong: Other refreshes succeeded, so gateway was online.
- C
The refresh exceeded the timeout limit set in the gateway.
Long refresh duration and failure suggest timeout.
- D
The data source was unavailable.
Why wrong: Other refreshes succeeded, so data source was available.
You need to ensure that a Power BI report uses the latest data from a cloud-based Azure SQL Database. The report is configured with scheduled refresh. What is the minimum required license for the dataset owner to configure a scheduled refresh?
Trap 1: Power BI Premium capacity
Capacity is not a license; users still need Pro.
Trap 2: Power BI Premium Per User
PPU is not minimum; Pro suffices.
Trap 3: Power BI Free
Free license cannot schedule refresh.
- A
Power BI Premium capacity
Why wrong: Capacity is not a license; users still need Pro.
- B
Power BI Premium Per User
Why wrong: PPU is not minimum; Pro suffices.
- C
Power BI Free
Why wrong: Free license cannot schedule refresh.
- D
Power BI Pro
Pro license is required to schedule refresh in shared capacity.
You manage a Power BI workspace used by the sales team. After updating a dataset with new columns, some users report that their reports show old data. You verify that the scheduled refresh completed successfully. What should you do first?
Trap 1: Clear the users' browser cache.
Clearing browser cache does not resolve schema mismatch issues.
Trap 2: Reconfigure the scheduled refresh to run more frequently.
Scheduled refresh already completed; frequency is not the problem.
Trap 3: Reset the on-premises data gateway.
The gateway is used for data source connectivity, not for dataset schema updates.
- A
Open the report in Power BI Desktop, refresh the dataset, and republish.
Updating the dataset in Desktop and republishing ensures the report uses the new schema.
- B
Clear the users' browser cache.
Why wrong: Clearing browser cache does not resolve schema mismatch issues.
- C
Reconfigure the scheduled refresh to run more frequently.
Why wrong: Scheduled refresh already completed; frequency is not the problem.
- D
Reset the on-premises data gateway.
Why wrong: The gateway is used for data source connectivity, not for dataset schema updates.
You are troubleshooting connectivity to a Power BI Premium dataset via the XMLA endpoint. A user reports that they cannot connect using SQL Server Management Studio (SSMS) but can view reports in the Power BI service. The user's email is user3@contoso.com. What is the most likely cause?
Exhibit
Refer to the exhibit.
Power BI XMLA endpoint configuration:
{
"allowedUsers": [
"user1@contoso.com",
"user2@contoso.com"
],
"allowAzureAnalysisServicesConnections": true,
"blockExternalConnections": false
}Trap 1: External connections are blocked by the configuration.
blockExternalConnections is false.
Trap 2: The user does not have permission to view reports.
They can view reports.
Trap 3: The XMLA endpoint is disabled.
The configuration shows it is enabled.
- A
External connections are blocked by the configuration.
Why wrong: blockExternalConnections is false.
- B
The user does not have permission to view reports.
Why wrong: They can view reports.
- C
The user is not in the allowedUsers list for the XMLA endpoint.
Only user1 and user2 are allowed.
- D
The XMLA endpoint is disabled.
Why wrong: The configuration shows it is enabled.
You publish a Power BI report to a workspace that uses an organizational app. After updating the report, you want users to see the changes immediately without having to reinstall the app. What should you do?
Trap 1: Delete and recreate the app from the workspace.
Deleting the app would cause users to lose access; they would need to reinstall.
Trap 2: Republish the report from Power BI Desktop.
Republishing the report does not automatically update the app.
Trap 3: Ask users to refresh their browser cache.
Browser cache may help but the app content is not automatically updated.
- A
Delete and recreate the app from the workspace.
Why wrong: Deleting the app would cause users to lose access; they would need to reinstall.
- B
Republish the report from Power BI Desktop.
Why wrong: Republishing the report does not automatically update the app.
- C
Ask users to refresh their browser cache.
Why wrong: Browser cache may help but the app content is not automatically updated.
- D
Update the app in the workspace by selecting 'Update app'.
Updating the app publishes changes to all users.
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?
Trap 1: Remove all scheduled refreshes and rely solely on the XMLA script.
This does not prevent concurrent XMLA script runs from different sessions.
Trap 2: Change the XMLA script to run less frequently, e.g., once per week.
Reducing frequency doesn't resolve the concurrency issue when multiple runs occur simultaneously.
Trap 3: Partition the dataset and refresh partitions sequentially.
Partitioning helps with performance but doesn't address the concurrency conflict.
- A
Remove all scheduled refreshes and rely solely on the XMLA script.
Why wrong: This does not prevent concurrent XMLA script runs from different sessions.
- B
Enable the 'Refresh conflict detection' setting on the dataset to prevent concurrent operations.
This setting detects and blocks overlapping refresh operations, preventing the error.
- C
Change the XMLA script to run less frequently, e.g., once per week.
Why wrong: Reducing frequency doesn't resolve the concurrency issue when multiple runs occur simultaneously.
- D
Partition the dataset and refresh partitions sequentially.
Why wrong: Partitioning helps with performance but doesn't address the concurrency conflict.
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?
Exhibit
Refer to the exhibit.
{
"version": "1.0",
"datasetSettings": {
"refreshSchedule": {
"frequency": "Daily",
"times": ["06:00", "18:00"],
"enabled": true,
"localTimeZone": "UTC"
},
"directQuery": {
"enableDirectQuery": false
}
},
"dataSources": [
{
"name": "SalesDB",
"connectionString": "Server=sqlsrv01;Database=Sales;Integrated Security=SSPI;",
"credentialType": "Windows",
"gatewayId": "gateway-cluster-01"
}
]
}Trap 1: The refresh schedule uses UTC but the data source is in a different…
Time zone mismatch would cause the refresh to happen at wrong local times, not fail.
Trap 2: The dataset has DirectQuery enabled, which prevents Import mode…
DirectQuery is explicitly disabled in the settings.
Trap 3: The gateway ID is incorrect.
The gateway ID is provided; if it were incorrect, the error would be different.
- A
The data source uses Integrated Security (SSPI) which is not supported for scheduled refresh.
SSPI requires the user's context; stored credentials cannot be used with SSPI.
- B
The refresh schedule uses UTC but the data source is in a different time zone.
Why wrong: Time zone mismatch would cause the refresh to happen at wrong local times, not fail.
- C
The dataset has DirectQuery enabled, which prevents Import mode refresh.
Why wrong: DirectQuery is explicitly disabled in the settings.
- D
The gateway ID is incorrect.
Why wrong: The gateway ID is provided; if it were incorrect, the error would be different.
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?
Trap 1: Enable the 'Reduce data shown in visuals' option in Power BI…
This option limits data displayed but does not reduce the load on the AAS model.
Trap 2: Implement row-level security (RLS) in the Azure Analysis Services…
RLS filters data but does not improve query performance.
Trap 3: Convert the report to import mode and schedule a refresh.
This changes the connection type and may not be desired; also requires a gateway.
- A
Enable the 'Reduce data shown in visuals' option in Power BI Desktop.
Why wrong: This option limits data displayed but does not reduce the load on the AAS model.
- B
Implement row-level security (RLS) in the Azure Analysis Services model.
Why wrong: RLS filters data but does not improve query performance.
- C
Deploy the Azure Analysis Services model to the same region as the Power BI workspace.
Reducing network latency between the data source and Power BI improves query response times.
- D
Convert the report to import mode and schedule a refresh.
Why wrong: This changes the connection type and may not be desired; also requires a gateway.
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