PL-300 Practice Test 48 — 15 Questions

Question 1

A company has a Power BI semantic model with a table named 'Sales' that contains columns: OrderDate, ShipDate, Quantity, and Revenue. The company wants to create a measure that calculates the total revenue for orders shipped within 7 days of the order date. Which DAX expression should be used?

Accepted Answer

CALCULATE(SUM(Sales[Revenue]), DATEDIFF(Sales[OrderDate], Sales[ShipDate], DAY) <= 7). Option A is correct because it uses CALCULATE to modify the filter context, applying a filter condition that uses DATEDIFF to compute the number of days between OrderDate and ShipDate. The condition `<= 7` correctly identifies orders shipped within 7 days, and SUM aggregates the Revenue column under that filtered context.

Answer

SUMX(FILTER(Sales, Sales[ShipDate] - Sales[OrderDate] <= 7), Sales[Revenue])

Answer

CALCULATE(SUM(Sales[Revenue]), DATEDIFF(Sales[OrderDate], Sales[ShipDate], DAY) <= 7)

Answer

CALCULATE(SUM(Sales[Revenue]), Sales[ShipDate] - Sales[OrderDate] <= 7)

Question 2

You are designing a Power BI semantic model for a retail company. The model must support reporting on sales by product, store, and date. You need to decide on the modeling approach. Which TWO actions should you take? (Select exactly two.)

Accepted Answer

Create a separate date dimension table and mark it as a date table.. Option A is correct because creating a separate date dimension table and marking it as a date table enables time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) to work correctly in DAX. This also ensures that the date column is recognized as a continuous date hierarchy, allowing proper filtering and slicing by year, month, and quarter across all fact tables.

Answer

Add calculated columns for year, month, and quarter to the Sales table.

Answer

Create relationships between tables using the foreign key columns.

Answer

Combine all data into a single flat table to simplify the model.

Question 3

Drag and drop the steps to create a quick measure in Power BI Desktop into the correct order.

Question 4

Drag and drop the steps to create a date table in Power BI Desktop using DAX into the correct order.

Question 5

You are reviewing a Power Query M script used to create a table in Power BI. The script imports data from SQL Server, filters for orders in 2022, groups by ProductID to sum revenue, sorts descending, and takes the top 10. However, the table loads slowly. You need to improve performance. Which change should you make?

Accepted Answer

Modify the script to use a native SQL query that performs the filtering and aggregation on the server side.. Option C is correct because pushing filtering, grouping, and aggregation to SQL Server via a native query reduces the volume of data transferred to Power BI and leverages the database engine's optimized execution. This minimizes memory and processing overhead in Power Query, directly addressing the slow load time caused by performing these operations on imported data.

Answer

Add a Table.Buffer step before the filter to speed up subsequent operations.

Answer

Remove the sorting step because it is unnecessary for the final table.

Answer

Combine the filter, group, and sort into a single step using Table.Buffer.

Question 6

Match each Power BI service feature to its description.

Question 7

Match each Power BI security feature to its purpose.

Question 8

Which TWO of the following are best practices for designing a data model in Power BI?

Accepted Answer

Use surrogate keys (integer IDs) for relationships instead of natural keys.. Option C is correct because using surrogate keys (integer IDs) instead of natural keys improves relationship performance and reduces storage overhead. Integer joins are faster than string or composite key joins, and surrogate keys avoid issues with changing natural key values, ensuring referential integrity and stable model relationships.

Answer

Use calculated columns to perform all transformations.

Answer

Set all relationships to bidirectional cross-filtering to avoid ambiguity.

Answer

Reference other queries as a single source to avoid duplication.

Question 9

A data modeler is creating a Power BI semantic model for a retail company. The model includes a 'Products' dimension table with columns ProductID, ProductName, Category, and Subcategory. The 'Sales' fact table has columns ProductID, Date, Quantity, and Revenue. The modeler wants to ensure that users can filter by Category and Subcategory. Which relationship type should be created between Products and Sales?

Accepted Answer

One-to-many (Products to Sales). In a Power BI semantic model, a one-to-many relationship from Products (the dimension table) to Sales (the fact table) is the standard star schema design. This allows users to filter Sales data by any attribute in Products, such as Category and Subcategory, because each ProductID in Products is unique (the 'one' side) and can be associated with many rows in Sales (the 'many' side). This relationship type ensures proper cross-filtering and aggregation behavior.

Answer

Many-to-one (Sales to Products)

Answer

Many-to-many

Answer

One-to-one

Question 10

A Power BI developer is designing a data model for sales analysis. The model includes a Sales fact table and dimension tables: Product, Customer, Date, and Store. Which TWO design considerations are best practices for optimizing query performance?

Accepted Answer

Create a separate date table and mark it as a date table to enable time intelligence functions.. Option C is correct because creating a separate date table and marking it as a date table enables Power BI to use built-in time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) that rely on a continuous, contiguous date range. This design ensures optimal performance by allowing the engine to generate efficient DAX queries and leverage date-based relationships without ambiguity.

Answer

Configure bidirectional cross-filtering between all dimension tables and the fact table.

Answer

Use multiple inactive relationships between fact and dimension tables to support different analyses.

Answer

Use many-to-many relationships between dimension tables and the fact table to simplify the model.

Question 11

A Power BI developer creates a star schema with a fact table Sales and dimension tables Customer, Product, Date. The relationship between Sales and Date is active. The developer wants to create a measure that calculates the total sales for the previous month relative to any selected month. Which DAX expression should the developer use?

Accepted Answer

CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Date[Date])). Option D is correct because PREVIOUSMONTH(Date[Date]) returns a set of dates for the full previous month relative to the last date in the current filter context. When wrapped in CALCULATE, it shifts the filter on the Date dimension to the prior month, correctly computing total sales for the previous month regardless of the selected month.

Answer

CALCULATE(SUM(Sales[Amount]), DATESMTD(Date[Date]))

Answer

CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR(Date[Date]))

Answer

CALCULATE(SUM(Sales[Amount]), DATEADD(Date[Date], -1, MONTH))

Question 12

A Power BI data model includes a table 'Orders' with columns OrderID, CustomerID, OrderDate, SalesAmount. The model also has a 'Date' table and a 'Customer' table. The relationships are: Orders[CustomerID] -> Customer[CustomerID] (many-to-one, single direction) and Orders[OrderDate] -> Date[Date] (many-to-one, single direction). A user creates a measure that sums SalesAmount and then filters by a slicer on Customer[City]. The slicer works correctly. However, when the user adds another slicer on Date[Year], the measure does not respect both slicers simultaneously. What is the most likely cause?

Accepted Answer

The measure might be using ALL or ALLEXCEPT that removes the filter context from the Date table.. Option D is correct because the measure likely uses ALL or ALLEXCEPT, which removes the filter context from the Date table. Even though the relationships are correctly configured and filters from the Date slicer propagate to Orders via the single-direction relationship, if the measure explicitly ignores those filters using a function like ALL(Date[Year]) or ALLEXCEPT(Orders, ...), the Date slicer will have no effect on the measure. This is a common DAX mistake where filter removal functions override slicer selections.

Answer

The Customer and Date tables are not related to each other.

Answer

The relationship between Orders and Date is inactive.

Answer

The relationships are set to single direction, so filters from Date do not propagate to Orders.

Question 13

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model includes a large fact table with 100 million rows. Users are experiencing slow report performance. Which THREE actions should the developer take to improve query performance?

Accepted Answer

Configure incremental refresh to limit data retrieved per query.. Option A is correct because incremental refresh limits the amount of data retrieved per query by partitioning the fact table into smaller, manageable date ranges. In a DirectQuery model, this reduces the volume of data scanned by SQL Server for each query, directly improving report performance by minimizing the data transfer and query execution time.

Answer

Hide columns that are not needed in reports.

Answer

Add calculated columns to precompute aggregations.

Question 14

A Power BI developer is building a data model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, ShipDate, SalesAmount. The developer wants to analyze orders by both order date and ship date. Which THREE actions should the developer take to properly model this scenario?

Accepted Answer

Use the USERELATIONSHIP function in DAX measures to specify which relationship to use for a given calculation.. Option A is correct because the USERELATIONSHIP function in DAX allows the developer to temporarily activate an inactive relationship for a specific calculation. In this scenario, one relationship (e.g., between Orders[OrderDate] and a date table) is active, while the other (e.g., between Orders[ShipDate] and the same or another date table) is inactive. By using USERELATIONSHIP in measures, the developer can specify which relationship to use for filtering or aggregation, enabling analysis by both order date and ship date without altering the model's default behavior.

Answer

Merge the OrderDate and ShipDate columns into a single column and use a flag to differentiate.

Answer

Use a single date table with an active relationship to OrderDate and an inactive relationship to ShipDate.

Question 15

A data analyst is designing a star schema in Power BI. The model includes a table named 'Orders' with columns: OrderID, CustomerID, OrderDate, ProductID, Quantity, and SalesAmount. Which column should NOT be included in the fact table to maintain a proper star schema?

Accepted Answer

CustomerID. In a star schema, fact tables store quantitative, measurable data (measures) and foreign keys to dimension tables. CustomerID is a descriptive attribute that belongs in a Customer dimension table, not in the fact table. Including it in the fact table would violate normalization principles and reduce the model's flexibility for filtering and hierarchy navigation.

Answer

Quantity

Answer

SalesAmount

Answer

OrderID