PL-300 Visualize and analyze the data — 20 Questions

Question 1

A Power BI report uses a measure that calculates Year-over-Year sales growth. Users report that the measure shows incorrect values for January 2024 when compared to January 2023. The data model contains a Date table with a continuous date range from January 1, 2020 to December 31, 2024. Which DAX function is most likely causing the issue?

Accepted Answer

SAMEPERIODLASTYEAR. SAMEPERIODLASTYEAR is the most likely cause of the issue because it returns a set of dates from the previous year that exactly matches the current period's date range. For January 2024, it will return January 1–31, 2023, but if the Date table does not have a full contiguous range (e.g., missing weekends or holidays), or if the measure relies on a different granularity, the comparison may produce incorrect values. The other functions shift dates differently or return entire periods, which can cause mismatches in Year-over-Year calculations.

Answer

PARALLELPERIOD

Answer

DATEADD

Answer

PREVIOUSYEAR

Question 2

A company wants to create a Power BI report that shows sales performance by region. The data contains a table 'Sales' with columns: Date, Amount, RegionID, and ProductID. They also have a 'Regions' table with RegionID and RegionName. They want to display a matrix visual with RegionName on rows and Year on columns, with the sum of Amount as values. However, the report displays only 'RegionID' instead of 'RegionName'. What is the most likely cause?

Accepted Answer

There is no active relationship between the Sales and Regions tables.. Option D is correct because if there is no active relationship between the Sales and Regions tables, Power BI cannot use the RegionName from the Regions table to filter or group the Sales data. Instead, it defaults to displaying the RegionID from the Sales table, which is the only related field available in the visual. An active relationship must exist between the two tables on the RegionID columns for RegionName to appear in the matrix.

Answer

The relationship is configured as many-to-many.

Answer

The relationship direction is set to Both.

Answer

The RegionID column in the Sales table is hidden.

Question 3

A Power BI report includes a bar chart showing total sales by product category. The report designer wants to add a trend line to the chart to show the overall sales trend over time. Which type of visual should be used instead?

Accepted Answer

Line chart. A line chart is the correct visual to show a trend over time because it plots data points connected by straight lines, making it easy to see the overall direction and pattern of total sales across a continuous time axis. Bar charts, including stacked variants, are designed for comparing discrete categories, not for displaying continuous trends.

Answer

Stacked bar chart

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Scatter chart

Answer

Pie chart

Question 4

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?

Accepted Answer

There is no visual-level filter to exclude blank values.. Option D is correct because the table visual is showing all employees due to the absence of a visual-level filter to exclude blank or zero sales amounts. In Power BI, a one-to-many relationship between Employee and Sales means that employees without sales will still appear in the visual unless explicitly filtered out, as the relationship does not automatically suppress rows from the 'one' side when there are no matching rows on the 'many' side.

Answer

The EmployeeID column in the Employee table is hidden.

Answer

The relationship is many-to-one, not one-to-many.

Answer

The relationship direction is set to Single from Employee to Sales.

Question 5

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?

Accepted Answer

CALCULATE(SUM(Sales[Amount]), DATESBETWEEN('Date'[Date], MAX('Date'[Date]) - 365, MAX('Date'[Date]))). Option A is correct because it uses DATESBETWEEN to define a custom date range from 365 days before the last date in the current filter context (MAX('Date'[Date])) up to that last date, effectively creating a rolling 12-month window. This approach works with a continuous date table and respects the filter context, ensuring the running total is calculated dynamically based on the latest visible date.

Answer

CALCULATE(SUM(Sales[Amount]), DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -12, MONTH))

Answer

TOTALMTD(SUM(Sales[Amount]), 'Date'[Date])

Answer

CALCULATE(SUM(Sales[Amount]), DATESYTD('Date'[Date]))

Question 6

A Power BI report includes a slicer for 'Year' and a line chart showing monthly sales. The report designer wants to ensure that when a user selects a year in the slicer, the line chart shows only the months of that year, with month names on the x-axis sorted chronologically. Which TWO actions must be taken?

Accepted Answer

Mark the Date table as a date table in the model.. Option A is correct because marking the Date table as a date table ensures that Power BI recognizes the table as containing a contiguous date range, which is required for time intelligence functions and proper date-based filtering. When a slicer filters by Year, the line chart must respect the date relationship; without a marked date table, the filter may not propagate correctly to the month level, and the x-axis may not display months in chronological order.

Answer

Create a date hierarchy with Year and Month.

Answer

Set the slicer to 'Single select' mode.

Answer

Hide the Month column in the Date table.

Question 7

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?

Accepted Answer

Use FILTER to filter the Orders table based on the condition.. Option A is correct because FILTER is necessary to iterate over the Orders table and apply a row-by-row condition to identify orders shipped within 3 days. In DAX, FILTER returns a table that can be used as a filter argument inside CALCULATE, enabling context transition and dynamic filtering. Without FILTER, you cannot evaluate the date difference condition for each row individually.

Answer

Use COUNTROWS without any filter.

Answer

Use SUM to add up the Amount column.

Question 8

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?

Accepted Answer

Create a separate date dimension table and relate it to the fact table. Creating a separate date dimension table and relating it to the fact table improves performance by enabling star schema design, which optimizes DirectQuery queries. Without a dedicated date table, Power BI may generate inefficient queries that scan the entire fact table for date filtering. A date dimension also supports time intelligence functions and reduces query complexity by allowing the database to use indexes on the date key.

Answer

Increase the date range filter to include more data

Answer

Disable cross-filtering in the report

Answer

Remove unnecessary columns from the date table

Question 9

A Power BI report uses a composite model with a DirectQuery source and an imported table. The imported table has many rows, and the report is taking a long time to refresh. What is the most likely cause?

Accepted Answer

The imported table is set to Dual storage mode, causing dependency on the DirectQuery source. In a composite model, when an imported table is set to Dual storage mode, it behaves as both Import and DirectQuery. During refresh, Power BI must check the DirectQuery source for consistency, which can significantly slow down the refresh process, especially with large imported tables. This dependency on the DirectQuery source is the most likely cause of the long refresh time.

Answer

Measures are using CALCULATE with multiple filter conditions

Answer

The DirectQuery table is set to Import storage mode

Answer

The report contains many complex visuals that need to be rendered

Question 10

You need to create a measure that calculates the year-over-year growth percentage for sales. Which DAX function should you use?

Accepted Answer

SAMEPERIODLASTYEAR. The SAMEPERIODLASTYEAR function is the correct choice for calculating year-over-year growth because it shifts the current filter context back by one year, returning a set of dates exactly one year prior. This allows you to compute the prior year's sales and then derive the growth percentage using a formula like (Current Sales - Prior Year Sales) / Prior Year Sales.

Answer

DATEADD

Answer

PARALLELPERIOD

Answer

PREVIOUSYEAR

Question 11

A company uses Row-Level Security (RLS) in Power BI. They want to ensure that when a manager views the report, they see data for their own region plus any region where a salesperson reports to them. Which RLS approach should you implement?

Accepted Answer

Use a DAX filter that references the USERPRINCIPALNAME() function. Option A is correct because Row-Level Security (RLS) in Power BI uses DAX filters that can dynamically evaluate the current user's identity via USERPRINCIPALNAME() or USERNAME(). By creating a DAX rule that checks whether the manager's UPN matches the region manager or if the salesperson's manager UPN equals the current user, you can enforce dynamic, hierarchical data access without hardcoding roles per manager.

Answer

Use Power BI App permissions to restrict data

Answer

Create a static role for each manager and assign users

Answer

Apply RLS at the visual level using bookmarks

Question 12

A Power BI report contains a page with many visuals that use a large DirectQuery dataset. The report is slow to load. Which design change would most improve the initial page load time?

Accepted Answer

Reduce the number of visuals on the page. Reducing the number of visuals on the page directly decreases the number of queries sent to the DirectQuery source during initial page load. Each visual in a DirectQuery model typically generates at least one separate query against the source database, so fewer visuals means fewer concurrent queries and less data transferred, which significantly improves load time.

Answer

Increase the default page-level filter to limit data

Answer

Use a slicer to let users choose what to see

Answer

Create aggregations on the dataset

Question 13

Which TWO are valid ways to create a calculated table in Power BI?

Accepted Answer

CALENDARAUTO(). Option D is correct because `CALENDARAUTO()` is a dedicated DAX function that automatically generates a single-column calculated table containing a contiguous range of dates based on the data model's date columns. This is a standard and valid method for creating a calculated table in Power BI, commonly used for time intelligence calculations.

Answer

VALUES(Customer[Country])

Answer

CALCULATE(SUM(Sales[Amount]), ALL(Sales))

Answer

FILTER(Products, Products[Color] = "Red")

Question 14

Which THREE are required components of a Power BI Paginated Report?

Accepted Answer

A dataset. A dataset is a required component of a Power BI Paginated Report because it defines the schema and structure of the data that the report renders. Without a dataset, the report has no data to display, making it impossible to generate any paginated output. The dataset is bound to a data source and provides the fields used in report items like tables, charts, and text boxes.

Answer

A subscription

Answer

A map visual

Answer

A query parameter

Question 15

A Power BI developer writes the Power Query M code shown in the exhibit. The code runs successfully but returns an error when the user selects a year from a slicer in the report. The error states: 'Expression.Error: The key did not match any rows in the table.' Which is the most likely cause?

Accepted Answer

The code hardcodes the year 2021, but the slicer passes a different year, causing the M code to fail when the source is queried. Option B is correct because the error 'The key did not match any rows in the table' occurs when a Power Query M query uses a hardcoded value (e.g., 2021) in a filter or lookup step, but the slicer passes a different year value to the report. When the slicer changes the parameter, the M code tries to retrieve data for that year, but the hardcoded key does not exist in the source table, causing the key lookup to fail. This is a classic parameterization issue where the M code should use a dynamic reference to the slicer value instead of a literal.

Answer

The table name Sales does not exist in the database

Answer

The ProductID column has duplicate values

Answer

The data type of the Year column is text instead of number

Question 16

A Power BI admin applies the Azure Policy shown in the exhibit. What is the effect of this policy?

Accepted Answer

Only users in the finance workspace can read datasets. The Azure Policy in the exhibit is configured to deny the 'Read' permission on datasets for all users except those in the 'finance' workspace. This means only users who are members of the finance workspace can read datasets, while all other users are denied read access. Therefore, option D is correct because it accurately describes that only users in the finance workspace can read datasets.

Answer

No one can read any datasets

Answer

Users cannot read datasets in the finance workspace

Answer

All users can read datasets in all workspaces

Question 17

A sales manager wants to create a report that shows year-over-year growth for each product category. They have a date table and a sales table with daily sales. Which DAX measure should they use to calculate the previous year's sales?

Accepted Answer

Sales PY = CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR(Date[Date])). Option C is correct because SAMEPERIODLASTYEAR is the most straightforward and reliable DAX function for calculating the previous year's sales when you have a proper date table. It automatically shifts the current filter context back by one year, ensuring that the measure returns the exact same period (e.g., same month and day range) from the prior year, which is ideal for year-over-year growth calculations.

Answer

Sales PY = CALCULATE(SUM(Sales[Amount]), DATEADD(Date[Date], -1, YEAR))

Answer

Sales PY = CALCULATE(SUM(Sales[Amount]), PARALLELPERIOD(Date[Date], -1, YEAR))

Answer

Sales PY = CALCULATE(SUM(Sales[Amount]), PREVIOUSYEAR(Date[Date]))

Question 18

A Power BI report shows a bar chart with sales by region. When users click on a region, they expect a line chart on the same page to filter to that region's sales over time. However, the line chart does not respond to the click. What is the most likely cause?

Accepted Answer

The interaction between the bar chart and line chart is set to 'None'.. Option A is correct because in Power BI, visual interactions control how one visual affects another when clicked. By default, cross-filtering and cross-highlighting are enabled, but if the interaction between the bar chart and line chart is explicitly set to 'None', clicking a region on the bar chart will not filter or highlight the line chart. This is the most common cause when a visual fails to respond to clicks on another visual.

Answer

The line chart uses a continuous axis that cannot be filtered.

Answer

The bar chart is not set as a slicer.

Answer

The line chart has a legend with too many items.

Question 19

A company has a dataset with a table 'Orders' containing columns: OrderDate, CustomerID, Amount. They want to create a visual that shows the total amount per month. Which of the following is the best approach?

Accepted Answer

Create a line chart with OrderDate on the axis and use the date hierarchy to drill down to month.. Option B is correct because it leverages Power BI's built-in date hierarchy, which automatically groups OrderDate by year, quarter, month, and day. By placing OrderDate on the axis of a line chart and drilling down to the month level, you get an accurate monthly aggregation of Amount without needing any manual data transformation or calculated columns. This approach is efficient, maintains the underlying data model's integrity, and allows for easy drill-up/drill-down navigation.

Answer

Create a pie chart with OrderDate as the legend.

Answer

Create a table visual with OrderDate and Amount, then group by month in the visual.

Answer

Create a bar chart with a calculated column 'Month' extracted from OrderDate and use that as the axis.

Question 20

Which TWO of the following are valid ways to create a measure in Power BI?

Accepted Answer

From the Modeling tab, click New Measure.. Option A is correct because the Modeling tab in Power BI Desktop provides a dedicated 'New Measure' button that allows users to create calculated measures using DAX (Data Analysis Expressions). This is the primary and most direct method for adding measures to your data model, enabling dynamic aggregations and calculations that are not stored in the table but computed at query time.

Answer

From the Format pane, add a measure.

Answer

From Power Query Editor, add a custom column.

Answer

From the Visualizations pane, click New Measure.