Microsoft Power BI Data Analyst PL-300 practice test

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.

Question 2hardmulti select

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.

Question 3mediummultiple choice

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.

Question 4hardmultiple choice

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.

Question 5mediummultiple choice

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.

Question 6mediummulti select

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.