Select Two (Multi-Select) Questions

Use the Quick Measure feature to create a 'Year-over-year change' measure.

Why wrong: Quick measures are optional, not required.

Apply the CALCULATE function to switch between years.

Why wrong: CALCULATE modifies filter context but is not specific to year comparison.

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.

Use COUNTROWS without any filter.

Why wrong: COUNTROWS without filter counts all orders, not just those shipped within 3 days.

Use SUM to add up the Amount column.

Why wrong: SUM adds values, not counts; we need to count rows.

From the Format pane, add a measure.

Why wrong: The Format pane is for visual formatting.

From Power Query Editor, add a custom column.

Why wrong: Power Query is for data transformation, not measures.

From the Visualizations pane, click New Measure.

Why wrong: The Visualizations pane does not have this option.

Create a Power BI Premium capacity to ensure high availability.

Why wrong: Premium capacity does not bypass gateway dependency.

Schedule the dataset refresh to run during the maintenance window.

Why wrong: This would fail if the gateway is offline.

Use DirectQuery instead of Import mode to avoid gateway dependency.

Why wrong: DirectQuery still requires gateway for on-premises sources.

Create a new workspace manually in production.

Why wrong: Pipelines create workspaces automatically.

Assign Power BI Pro licenses to all developers.

Why wrong: Licenses are prerequisite, not part of deployment steps.

The number of visuals per report page.

Why wrong: This is a report design concern, not deployment infrastructure.

The currency format used in reports for each region.

Why wrong: Formatting is a report design consideration, not deployment.

Assign the dataset owner to each stage workspace.

Why wrong: Dataset ownership is not changed by pipelines automatically.

Re-enter data source credentials for each stage after deployment.

Why wrong: Credentials must be configured, but this is done separately, not a required action for setting up pipeline data source switching.

Create separate gateways for each stage.

Why wrong: A single gateway can serve multiple stages with proper configuration.

Normalize the data warehouse tables

Why wrong: Normalization increases joins, degrading performance.

Switch the dataset to Import mode

Why wrong: This changes the connectivity mode, not a performance optimization within DirectQuery.

Merge the Customer and Product dimensions into one table to reduce the number of tables.

Why wrong: Merging dimensions contradicts star schema principles and can cause data duplication.

Keep all columns in a single table to avoid relationships.

Why wrong: A single table is not a star schema; it leads to redundancy and poor performance.

Use 'Split Column' to divide a column into multiple columns based on a delimiter.

Why wrong: Split Column is indeed a transformation, but the question asks for TWO correct methods; only B and D are correct among the options listed as per the explanation.

Use 'Merge Queries' to combine rows from multiple tables based on a key.

Why wrong: Merge combines columns, not rows; it is a transformation but not described correctly.

Use 'Append Queries' to combine columns from two tables.

Why wrong: Append combines rows, not columns.

Split the column by delimiter '<' and then extract the first part.

Why wrong: This may not work for complex HTML.

Remove the columns containing HTML tags.

Why wrong: You need the data, not remove it.

Use the 'Clean' function to remove all HTML tags.

Why wrong: Clean removes non-printable characters, not HTML.

Enable encryption at rest for the dataset.

Why wrong: Encryption at rest protects data from unauthorized physical access but does not control user permissions.

Use Power Query to mask PII columns by replacing values with '***'.

Why wrong: Masking in Power Query is static and applies to all users; it does not provide granular access control.

Apply sensitivity labels to the dataset.

Why wrong: Sensitivity labels classify data but do not enforce access restrictions at the row level.

Sort data in ascending order to improve compression.

Why wrong: Sorting does not significantly improve performance and may add overhead.

Merge queries before filtering.

Why wrong: Merging large tables first may cause slow performance; filter first if possible.

Filter rows based on a date column.

Why wrong: Filtering usually folds.

Remove columns.

Why wrong: Removing columns folds.

Rename a column.

Why wrong: Renaming is foldable.

Excel workbook

Why wrong: Excel workbooks only support import mode.

CSV file

Why wrong: CSV files only support import mode.

SharePoint list

Why wrong: SharePoint lists typically use import mode, though limited DirectQuery is available via dataflows.

Use 'Reverse Rows'

Why wrong: Reverses order, does not handle duplicates.

Use 'Sort Ascending'

Why wrong: Sorts data, does not handle duplicates.

SharePoint list

Why wrong: This is a valid source, but the question asks for exactly two; B and C are also valid.

Power BI dataset

Why wrong: Power BI dataset is a valid source via live connection, but not typically for Power Query import.

Microsoft Entra ID

Why wrong: This is an identity service, not a data source.

Use Windows authentication.

Why wrong: Windows authentication is not supported for Azure SQL Database.

Use SQL Server authentication with a strong password.

Why wrong: SQL authentication is less secure than Microsoft Entra ID authentication.

User license type (Pro vs Premium).

Why wrong: License affects sharing but not storage mode choice.

Report color scheme and branding.

Why wrong: Color scheme is unrelated to storage mode.

Avoid renaming columns in Power Query; use original names

Why wrong: Renaming can improve readability and maintainability.

Keep all columns from the source to avoid missing data

Why wrong: Keeping unnecessary columns increases model size and reduces performance.