PL-300 Practice Exam 63 — 20 Questions

Question 1

You have a Power BI report that displays key performance indicators (KPIs) using a KPI visual. The visual shows a measure 'Current Sales' with a goal of 'Target Sales'. You want to show the status (on track, behind, etc.) based on the difference. You configure the KPI visual with the measure, goal, and trend axis. However, the status indicator does not appear. What should you do? A. Ensure the measure and goal are both numeric and have the same unit. B. Add a trend line to the visual. C. Set the 'Direction' property to 'High is good' or 'Low is good'. D. Use a different visual like a gauge. Which option is the best?

Accepted Answer

Set the 'Direction' property to 'High is good' or 'Low is good'. Option C is correct because the KPI visual requires setting the direction to calculate status. Option A is wrong because units don't need to be same. Option B is wrong because trend line is optional. Option D is wrong because gauge is an alternative but not a fix for KPI.

Answer

Add a trend line to the visual

Answer

Ensure the measure and goal are both numeric and have the same unit

Answer

Use a different visual like a gauge

Question 2

You are a Power BI analyst for a financial services company. You have a semantic model that contains a 'Transactions' fact table with millions of rows, and a 'Calendar' date dimension table. You need to create a report page that shows the year-to-date (YTD) total transaction amount compared to the same period last year (SPLY). The report must allow users to select a year from a slicer, and the YTD calculation should always be based on the maximum date in the data for the selected year (i.e., show YTD as of the latest available date). You have created the following measures:

- Total Amount = SUM(Transactions[Amount])
- YTD Amount = TOTALYTD([Total Amount], 'Calendar'[Date])
- SPLY YTD = CALCULATE([YTD Amount], SAMEPERIODLASTYEAR('Calendar'[Date]))

When users select a year from the slicer, the YTD Amount does not correctly show the YTD as of the last date in the selected year; instead, it shows the YTD for each individual date in the context. What is the most likely issue?

Accepted Answer

The YTD measure should be wrapped in a CALCULATE that filters to the last date in the selected period.. The TOTALYTD function calculates YTD for each date in the filter context. If the visual has a date field, it will show YTD for each date. To show a single YTD value as of the last date, you need to use a measure that filters to the last date. Option D is correct: you need to modify the measure to use LASTDATE or MAX to get the YTD as of the last date. Option A is incorrect because TOTALYTD is correct syntax. Option B is incorrect because the relationship is fine. Option C is incorrect because the issue is not with slicer interaction.

Answer

The relationship between Transactions and Calendar is not active.

Answer

The slicer is not configured to filter the Calendar table.

Answer

The TOTALYTD function is not appropriate; you should use DATESYTD instead.

Question 3

You are a data analyst for a retail company with stores across 50 states. You have a Power BI dataset that imports sales data from a SQL Server database daily. The fact table contains 200 million rows and includes columns: StoreID, ProductID, DateKey, SalesAmount, Quantity, and Discount. You also have dimension tables for Store, Product, and Date. Users report that a report page with a matrix visual showing SalesAmount by Store and ProductCategory takes over 30 seconds to render. You need to improve the performance of this visual without changing the data source or reducing the data granularity. You have the following options: A. Change the matrix visual to a table visual. B. Create an aggregation table on Store and ProductCategory with pre-calculated SalesAmount. C. Enable 'Show items with no data' on the matrix. D. Use a measure that sums SalesAmount and use the 'Filter' pane to restrict to top 100 rows. Which option should you choose?

Accepted Answer

Create an aggregation table on Store and ProductCategory with pre-calculated SalesAmount. Option B is correct because creating an aggregation table at a higher granularity (Store, ProductCategory) allows Power BI to use aggregated data for the visual, drastically reducing query time. Option A is wrong because a table visual does not improve performance; it may even be slower. Option C is wrong because showing items with no data increases the number of rows displayed. Option D is wrong because filtering to top 100 rows does not address the underlying query performance; the measure still scans the entire fact table.

Answer

Change the matrix visual to a table visual

Answer

Use a measure that sums SalesAmount and use the 'Filter' pane to restrict to top 100 rows

Answer

Enable 'Show items with no data' on the matrix

Question 4

You are a Power BI administrator for a large enterprise. You have a shared dataset that is used by multiple reports. The dataset contains sensitive financial data. You need to implement row-level security (RLS) so that managers can only see data for their own region. The dataset has a table 'Sales' with RegionID, and a table 'Managers' with ManagerID, ManagerName, and RegionID. You need to create an RLS role that filters the Sales table based on the logged-in user's region. You have the following options: A. Create a role with a DAX filter: 'Sales[RegionID] = USERPRINCIPALNAME()'. B. Create a role with a DAX filter: 'Sales[RegionID] = LOOKUPVALUE(Managers[RegionID], Managers[ManagerName], USERPRINCIPALNAME())'. C. Create a role with a DAX filter: 'Sales[RegionID] = USERNAME()'. D. Create a role with a static filter for each region. Which option should you choose?

Accepted Answer

Create a role with a DAX filter: 'Sales[RegionID] = LOOKUPVALUE(Managers[RegionID], Managers[ManagerName], USERPRINCIPALNAME())'. Option B is correct because it uses LOOKUPVALUE to find the region for the logged-in user (ManagerName) from the Managers table, and then filters Sales accordingly. Option A is wrong because RegionID is not a user principal name. Option C is wrong because USERNAME() returns the user's login name, not region. Option D is wrong because static filters would require multiple roles and manual maintenance.

Answer

Create a role with a DAX filter: 'Sales[RegionID] = USERNAME()'

Answer

Create a role with a DAX filter: 'Sales[RegionID] = USERPRINCIPALNAME()'

Answer

Create a role with a static filter for each region

Question 5

You are a Power BI developer for a retail company. You have a semantic model that includes a 'Sales' fact table with columns: 'Date', 'ProductID', 'StoreID', 'Quantity', 'UnitPrice'. The 'Product' dimension table includes 'ProductID', 'ProductName', 'Category', 'SubCategory'. The 'Store' dimension table includes 'StoreID', 'StoreName', 'Region', 'District'. You need to create a report page that allows users to analyze sales performance by product category and store region. The report must include a matrix visual with: - Rows: Product Category - Columns: Store Region - Values: Total Sales Amount (Quantity * UnitPrice) Additionally, users must be able to drill down from category to subcategory in the rows, and from region to district in the columns. You also need to ensure that when a user selects a specific store region, the matrix only shows data for that region and its districts. You have created the measures and the matrix visual. However, when you test the drill down, the hierarchy does not work as expected: clicking the expand icon on a category does not show subcategories. What is the most likely cause?

Accepted Answer

The matrix rows do not have a hierarchy defined; Category and SubCategory are separate fields.. For drill down to work in a matrix, the fields must be in a hierarchy. The correct approach is to use a hierarchy in the rows and columns. If the fields are simply placed as separate rows/columns, drill down won't work. Option A is correct because without a hierarchy, the expand button will not drill down. Option B is incorrect because the measure is defined correctly. Option C is incorrect because cross-filter direction doesn't affect drill down. Option D is incorrect because slicer interaction is not the issue.

Answer

The Total Sales measure is incorrectly defined, causing blank values for subcategories.

Answer

A slicer for Store Region is interfering with the matrix drill down behavior.

Answer

The relationship between Sales and Product is set to single direction, preventing drill through.

Question 6

You are a Power BI developer for a healthcare organization. You have a semantic model with a 'PatientVisits' fact table (columns: 'VisitID', 'PatientID', 'Date', 'Department', 'DurationMinutes', 'Cost') and a 'Patients' dimension table (columns: 'PatientID', 'Age', 'Gender', 'City'). You need to create a report page that shows the average cost per visit by department and age group. The age groups are: 0-18, 19-35, 36-50, 51-65, 65+. You want to use a custom visual that displays a matrix with departments as rows and age groups as columns, and the value as average cost. You have created a calculated column for age groups in the Patients table. However, when you place the age group column in the matrix columns, the values are not aggregated correctly; instead, each age group shows the same average cost as the overall average. What is the most likely cause?

Accepted Answer

The relationship between PatientVisits and Patients is many-to-many, causing ambiguous filter propagation.. The issue is that the age group column is from the Patients dimension, but the fact table does not have a direct relationship with the calculated column if the relationship is not properly set. However, more likely, the measure is not correctly referencing the fact table. Option C is correct: the measure should use AVERAGE of Cost from PatientVisits, but if the measure is defined as AVERAGE(PatientVisits[Cost]) without proper filter propagation, it might ignore the age group filter. But actually, the typical cause is that the calculated column is not being used in the visual correctly; the matrix might be grouping by the age group column, but the measure might be summing over all rows. Option B (measure uses SUM instead of AVERAGE) would cause higher values, not same. Option A (relationship is many-to-many) could cause issues but not necessarily same values. Option D (the age group column is not added to the visual level filter) is not relevant. The most likely is that the measure is not aggregated correctly because the age group column is from a different table and the filter context is not being transferred. But in a star schema, it should work. Another possibility: the age group column is a calculated column that uses a static reference, but the issue might be that the visual is not using the correct granularity. Actually, the correct answer is that the measure needs to be defined to use the relationship correctly. However, given the options, Option C (the measure uses SUM instead of AVERAGE) would produce different numbers, but not identical across groups. Option B (the relationship is many-to-many) could cause filter propagation issues. I'll choose B as the most likely.

Answer

The measure used is SUM of Cost instead of AVERAGE.

Answer

The age group column is not added to the matrix column field well; it should be in rows.

Answer

The age group calculated column is not part of the relationship chain; it is not being used as a filter.

Question 7

Your organization uses Power BI with a shared capacity. You have a dataset that is refreshed daily from an on-premises SQL Server database using an on-premises data gateway. The dataset contains sensitive financial data. The security team requires that all access to the dataset be logged and that any access from outside the corporate network be flagged. You need to implement a monitoring solution. What should you do?

Accepted Answer

Enable Power BI activity logging and stream to Azure Log Analytics, then create alerts on access events from external IPs.. Option B is correct because enabling Power BI activity logging and streaming to Azure Log Analytics allows querying and alerting on access events. Option A is wrong because the data gateway logs do not include access events. Option C is wrong because Microsoft Defender for Cloud Apps can provide conditional access but not logging of all access. Option D is wrong because Azure SQL Auditing is for database-level, not Power BI.

Answer

Audit the SQL Server database using Azure SQL Auditing.

Answer

Use Microsoft Defender for Cloud Apps to enforce conditional access policies.

Answer

Enable logging on the on-premises data gateway and monitor the logs.

Question 8

You have a Power BI workspace that contains several dashboards and reports. You need to ensure that the workspace is certified and that only certified datasets can be used in reports across the tenant. You also want to display a certification badge on the workspace. What should you do?

Accepted Answer

Apply certification to the datasets in the workspace via the dataset settings.. Option B is correct because certification is applied to datasets, not workspaces. The certification badge appears on datasets. Option A is wrong because certification is not a workspace-level setting. Option C is wrong because workspace description does not certify. Option D is wrong because that setting controls endorsement, not certification.

Answer

Update the workspace description to include 'Certified'.

Answer

Mark the workspace as 'Featured' in the admin portal.

Answer

Enable the 'Endorsement' setting for the workspace.

Question 9

You are a Power BI administrator for a small business. The company uses Power BI Pro licenses for all users. You need to ensure that all data sources used in Power BI reports are documented and that sensitive data is classified. You have been asked to set up a process that automatically scans Power BI datasets for sensitive data and adds classification labels. You have the following options:

A. Use Microsoft Purview to scan Power BI datasets and apply sensitivity labels.
B. Use Power BI's built-in data classification feature to manually label datasets.
C. Use Microsoft Sentinel to monitor data access and apply labels.
D. Use Azure Policy to enforce labeling on Power BI datasets.

Which option should you choose?

Accepted Answer

Use Microsoft Purview to scan Power BI datasets and apply sensitivity labels.. Option A is correct. Microsoft Purview can automatically scan Power BI datasets for sensitive data and apply sensitivity labels based on classification rules. Option B is wrong because manual labeling is not automatic. Option C is wrong because Microsoft Sentinel is a SIEM, not a data classification tool. Option D is wrong because Azure Policy does not directly integrate with Power BI for labeling.

Answer

Use Power BI's built-in data classification feature to manually label datasets.

Answer

Use Azure Policy to enforce labeling on Power BI datasets.

Answer

Use Microsoft Sentinel to monitor data access and apply labels.

Question 10

You are the Power BI administrator for Contoso Ltd. The company has a Premium capacity workspace named 'Sales Analytics' that contains a dataset named 'SalesData' and several reports. The dataset uses DirectQuery to an Azure SQL Database. Row-level security (RLS) is configured in Power BI Desktop with roles: 'SalesManager' (filters to SalesManager rows), 'SalesRep' (filters to SalesRep rows). After publishing, you assign users to the roles in the Power BI service. However, when a user assigned to the 'SalesRep' role opens a report, they see all data instead of only their own rows. You have verified that the RLS role definition is correct and that the user is the only member of the 'SalesRep' role. The user has no other workspace permissions. The dataset is set to use single sign-on (SSO) for the DirectQuery connection. What is the most likely cause of the issue?

Accepted Answer

Configure RLS in the Azure SQL Database itself using security predicates or views that filter based on the user's identity (e.g., USER_NAME() or SUSER_SNAME()).. Option A is correct because when using DirectQuery with SSO, the user's identity is passed to the data source. If the Azure SQL Database does not enforce RLS (e.g., via security predicates or user mappings), all data is returned. Power BI RLS is bypassed in this scenario. Option B is wrong because the user is not a workspace member with edit permissions. Option C is wrong because the user is the only member. Option D is wrong because RLS in Power BI works with DirectQuery, but SSO changes the behavior.

Answer

Add the user to multiple RLS roles to ensure the filters are applied.

Answer

Change the dataset storage mode from DirectQuery to Import.

Answer

Remove the user from the 'SalesRep' role and add them as a Viewer on the workspace to force RLS.

Question 11

Your Power BI workspace contains a dataset that uses a DirectQuery connection to Azure SQL Database. You need to ensure that only users with the 'Viewer' role in the workspace can query the dataset, but they should not be able to see the underlying SQL credentials. What should you do?

Accepted Answer

Configure the dataset to use a service principal with a credential stored in Power BI.. Option A is correct because using a service principal with a credential stored in Power BI ensures users do not see credentials. Option B is wrong because stored credentials are not visible to users. Option C is wrong because RLS does not hide credentials. Option D is wrong because OLS does not apply to credentials.

Answer

Use Windows authentication with the user's own credentials.

Answer

Use row-level security (RLS) to restrict query access.

Answer

Use object-level security (OLS) to hide the credential columns.

Question 12

You are a Power BI administrator for a large enterprise. The organization uses Microsoft Purview Information Protection sensitivity labels. You have enabled sensitivity labels in the Power BI admin portal and published labels in the Microsoft 365 Compliance Center. Users have been assigned the appropriate licenses. However, when a user tries to apply a sensitivity label to a report in the Power BI service, the label options are grayed out. The user has a Power BI Pro license and is a Member of the workspace where the report resides. The report is stored in a workspace that is backed by a Premium capacity. What is the most likely reason the user cannot apply the label?

Accepted Answer

The user does not have the required Azure Rights Management (Azure RMS) license or permissions to apply labels.. Option C is correct because to apply sensitivity labels in Power BI, the user must have the 'Azure Information Protection' (AIP) rights (e.g., 'Rights Management' or 'Protection') enabled. Even with a Pro license, if the user does not have the AIP add-on or the rights assigned, they cannot apply labels. Option A is wrong because the workspace is backed by Premium, but labels work in shared capacity too. Option B is wrong because the user is a Member, which allows editing. Option D is wrong because the labels are published.

Answer

The sensitivity labels have not been published to the user's security group.

Answer

The workspace is not enabled for sensitivity labels; you need to enable labels at the workspace level.

Answer

The user's role in the workspace is insufficient; they need at least Contributor role to apply labels.

Question 13

You are a Power BI administrator for a large enterprise. The company has a Power BI tenant with thousands of workspaces. You need to audit all shared links (shareable links) that have been created across the tenant to identify any that are shared with external users. You also need to revoke any links that were created more than 90 days ago. You want to use a PowerShell script to accomplish this efficiently. The script must output a CSV file with columns: LinkId, WorkspaceName, ReportName, CreatedDate, ExternalSharing. What should you do?

Accepted Answer

Use the Power BI REST API cmdlet Get-PowerBIShareableLink to retrieve and filter links by CreatedDate, then revoke with Remove-PowerBIShareableLink.. Option B is correct because the Power BI REST API (via PowerShell) can retrieve shareable links and filter by creation date. Option A is wrong because the admin portal lacks automation. Option C is wrong because Microsoft Graph API does not directly manage Power BI shareable links. Option D is wrong because Log Analytics does not provide shareable link metadata.

Answer

Enable Power BI activity logs and query Log Analytics for shareable links.

Answer

Use Microsoft Graph API to audit and manage Power BI shareable links.

Answer

Use the Power BI admin portal to manually export shareable links.

Question 14

You are a Power BI administrator for a large enterprise. The company has a Premium capacity (P3) that hosts over 200 datasets and 500 reports. Recently, users have reported that some reports take a long time to load, and the capacity metrics show high CPU usage during business hours. You need to optimize the capacity performance without adding additional capacity. The business requires that all reports remain available during business hours (9 AM to 5 PM). You have the following options:

A. Enable 'Autoscale' on the Premium capacity to automatically add additional v-cores during peak times.
B. Implement a 'Query caching' policy for frequently used datasets.
C. Move all datasets to shared capacity to reduce Premium load.
D. Schedule dataset refreshes to occur only during business hours.

Which option should you choose?

Accepted Answer

Implement a 'Query caching' policy for frequently used datasets.. Option B is correct. Query caching can improve report load times by caching query results for frequently used datasets, reducing CPU usage. Option A is wrong because Autoscale adds capacity but increases cost; the requirement is to optimize without adding capacity. Option C is wrong because shared capacity has lower performance limits and may not support the workload. Option D is wrong because scheduling refreshes during business hours would increase CPU usage during peak times.

Answer

Move all datasets to shared capacity to reduce Premium load.

Answer

Schedule dataset refreshes to occur only during business hours.

Answer

Enable 'Autoscale' on the Premium capacity to automatically add additional v-cores during peak times.

Question 15

Your organization uses Microsoft Power BI with Microsoft Purview for data governance. You have a dataset that contains customer data classified as 'Highly Confidential' under a sensitivity label. The compliance team requires that when this dataset is shared with external users, a Microsoft Purview data loss prevention (DLP) policy must block the sharing and notify the compliance team. You need to configure this. What should you do?

Accepted Answer

Create a DLP policy in Microsoft Purview that applies to Power BI and blocks sharing of content with the 'Highly Confidential' label.. Option A is correct because DLP policies in Microsoft Purview can block sharing based on sensitivity labels. Option B is wrong because Microsoft Defender for Cloud Apps is for app governance, not DLP. Option C is wrong because Power BI admin settings do not provide DLP. Option D is wrong because Microsoft Sentinel is for security monitoring, not DLP.

Answer

Use Microsoft Defender for Cloud Apps to create a session policy that blocks sharing.

Answer

Configure Microsoft Sentinel to monitor and block sharing events.

Answer

In the Power BI admin portal, disable sharing for workspaces containing 'Highly Confidential' content.

Question 16

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 enable bidirectional cross-filtering between the Date and Sales tables. Without this, slicers on the Date table (e.g., month) do not propagate filters to the Sales table, so the measure, which iterates over Sales rows, remains unaffected. Marking the Date table as a date table ensures that date hierarchies and slicers correctly filter related fact tables.

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 17

You are building a Power BI model for a logistics company. You have a table named 'Shipments' with columns: ShipmentID, OriginCity, DestinationCity, Weight, Cost, ShipDate, DeliveryDate. You also have a 'City' table with columns: CityName, State, Region. You create relationships: Shipments[OriginCity] to City[CityName] and Shipments[DestinationCity] to City[CityName]. Both relationships are active and many-to-one. You create a measure to calculate total cost:

TotalCost = SUM(Shipments[Cost])

When you use a slicer on City[State], you expect to filter shipments where either the origin or destination city is in that state. However, the filter only applies to the origin city due to the active relationship. You need to modify the model so that a single slicer on City[State] filters shipments where either origin or destination is in the selected state. What is the best approach?

Accepted Answer

Create two separate dimension tables: 'Origin' and 'Destination', each containing a copy of the City data. Then create active relationships from Shipments to each. Finally, create a new calculated table 'AllCities' that unions the city names and use that for the slicer, with measures that use USERELATIONSHIP to switch between relationships.. Option A is correct because it resolves the ambiguity of having two active relationships from Shipments to City by creating separate dimension tables for origin and destination, each with an active relationship. A calculated 'AllCities' table unions all city names for the slicer, and measures use USERELATIONSHIP to activate the appropriate relationship context, enabling a single slicer to filter shipments where either origin or destination city matches the selected state.

Answer

Remove the relationship for DestinationCity and use a DAX measure with LOOKUPVALUE to get the destination state.

Answer

Create a new table 'Route' that contains all unique combinations of origin and destination cities, and use that as a filter table.

Answer

Keep both relationships active and set the cross-filter direction to both.

Question 18

You are a data analyst for a retail company. You are building a Power BI model to analyze inventory levels across multiple warehouses. The source data is a SQL Server database with two tables: Inventory (WarehouseID, ProductID, StockOnHand, ReorderPoint) and Product (ProductID, ProductName, Category, UnitPrice). The Inventory table has 500,000 rows, and Product has 10,000 rows. You import both tables into Power BI. You need to create a measure that calculates the total value of inventory (StockOnHand * UnitPrice) for products that are below their reorder point. You create the following measure:

TotalValueBelowReorder = 
CALCULATE(
    SUMX(Inventory, Inventory[StockOnHand] * RELATED(Product[UnitPrice])),
    Inventory[StockOnHand] < Inventory[ReorderPoint]
)

However, the measure returns an incorrect total. You suspect an issue with the filter context. What is the most likely cause of the incorrect result?

Accepted Answer

The filter condition is applied to the entire Inventory table, but the row context from SUMX is not being considered, causing the filter to apply incorrectly.. Option B is correct because the filter condition `Inventory[StockOnHand] < Inventory[ReorderPoint]` is applied as a table-level filter on the entire Inventory table, not within the row context of SUMX. SUMX iterates over each row of Inventory, but the CALCULATE filter overrides the row context, causing the filter to be evaluated against the whole table rather than per row. This leads to an incorrect total because the condition is not evaluated for each individual product as intended.

Answer

SUMX cannot iterate over Inventory directly because it is a table reference; you need to use VALUES or a measure.

Answer

The measure needs to be written using SUM instead of SUMX because StockOnHand and UnitPrice are both numeric columns.

Answer

The RELATED function fails because the relationship between Inventory and Product is inactive.

Question 19

You are a data analyst at a retail company. You are building a Power BI report to analyze sales performance across stores. The data source is a SQL Server database with a table called 'SalesTransactions' containing 500 million rows. The table has columns: TransactionID, StoreID, ProductID, Quantity, UnitPrice, Discount, TransactionDate. You have imported the data into Power BI using Import mode. The report is slow when users filter by date or store. The initial data load took 45 minutes, and scheduled refreshes are failing because they exceed the 2-hour refresh limit. You need to reduce the refresh time and improve query performance. The business requires that users can see all historical data and that the report is always up-to-date (refreshed daily). What should you do?

Accepted Answer

Implement Incremental refresh with a policy to keep the last 5 years of data and detect changes.. Option B is correct because incremental refresh in Power BI allows you to partition large tables (like 500M rows) into smaller date-based ranges, refreshing only the most recent data (e.g., last 5 years) while keeping historical partitions static. This drastically reduces refresh time and avoids the 2-hour refresh limit, while still meeting the requirement for daily updates and full historical visibility. The 'detect changes' option further optimizes by only refreshing partitions where data has changed.

Answer

Create aggregations on the SalesTransactions table.

Answer

Switch to DirectQuery mode to avoid data import.

Answer

Use a live connection to the SQL Server database.

Question 20

You are working on a Power BI project for a marketing department. You have a CSV file with customer survey responses. The file contains columns: CustomerID, SurveyDate, Response (text with ratings from 1 to 5), Comments (free text). The file is 10 MB. You need to load the data into Power BI and create a measure that calculates the average rating. However, when you load the file, you notice that the Response column is imported as text instead of whole number. Also, there are some rows with missing values in the Response column. You need to ensure the data is correctly typed and handle missing values appropriately. What is the best approach?

Accepted Answer

Change the data type of Response to whole number in Power Query, then filter out or replace null values.. Option D is correct because Power Query is the designated tool for data type transformations and null handling during the load phase. Changing the Response column's data type to Whole Number in Power Query automatically converts valid text numbers and flags errors, while filtering out or replacing null values ensures clean data before the data model is built. This approach follows the best practice of performing data cleansing in Power Query rather than in DAX, which would add unnecessary overhead and complexity.

Answer

Use the 'Column from Examples' feature to create a new column with numeric values.

Answer

In Power Query, split the Response column by delimiter and then use the first part.

Answer

Use a DAX calculated column to convert text to number.