PL-300 Practice Test 19 — 15 Questions

Question 1

Refer to the exhibit. A Power BI developer wrote the DAX measure above to calculate year-over-year sales growth. When tested in a matrix visual with Year on rows and Month on columns, the measure returns incorrect results for the month of February in leap years. What is the likely cause?

Accepted Answer

SAMEPERIODLASTYEAR does not handle leap years correctly for February 29.. Option B is correct because SAMEPERIODLASTYEAR shifts the date context by exactly 365 days, which can cause issues in leap years for dates after February 28. Option A is incorrect because DIVIDE handles division by zero. Option C is incorrect because the measure is correctly defined as a measure. Option D is incorrect because the variable is fine.

Answer

The measure should be a calculated column, not a measure.

Answer

The variable CurrentSales is not needed; use SUM directly.

Answer

The DIVIDE function returns an error when PreviousSales is zero.

Question 2

You are modeling data for a retail company. The source data contains a table 'Transactions' with columns: TransactionID, StoreID, ProductID, Quantity, and SalesAmount. You need to create a star schema in Power BI. What should you do with the TransactionID column?

Accepted Answer

Keep TransactionID in the fact table. Option D is correct because TransactionID is a unique identifier for each transaction and should be kept in the fact table as a primary key. Option A is wrong because creating a separate dimension for TransactionID is unnecessary and would create a degenerate dimension. Option B is wrong because removing it loses granularity. Option C is wrong because it is not a dimension attribute.

Answer

Create a separate dimension table for transactions

Answer

Move TransactionID to the Product dimension

Answer

Remove the TransactionID column to reduce model size

Question 3

You have the above Power Query M script. What is the result of this transformation?

Accepted Answer

A table with one row per ProductID and columns: ProductID, TotalQty. Option D is correct because the script filters rows where OrderDate >= Jan 1 2023, removes the ProductDescription column, and groups by ProductID summing Quantity. The result is a table with one row per ProductID and a TotalQty column. Option A is wrong because it does not retain all columns. Option B is wrong because it aggregates. Option C is wrong because it does not keep individual rows.

Answer

A table with one row per ProductID and columns: ProductID, Quantity

Answer

A table with all sales rows for 2023 and columns: ProductID, Quantity

Answer

A table with all sales rows for 2023 and columns: OrderDate, ProductID, Quantity, TotalQty

Question 4

You have a Power BI data model that uses a DirectQuery connection to a SQL Server database. The model contains a fact table 'OrderDetails' with 50 million rows and a dimension table 'Products' with 10,000 rows. You need to create a measure that calculates the average order quantity per product. What is the best approach to optimize performance?

Accepted Answer

Use AVERAGEX over the Products table and sum the quantity for each product. Option C is correct because using AVERAGEX with the Products table reduces the number of rows processed; it calculates the average per product, which is more efficient than iterating over millions of rows. Option A is wrong because CALCULATE with FILTER on the fact table can be slow. Option B is wrong because calculated columns in DirectQuery are evaluated row by row and can degrade performance. Option D is wrong because creating an aggregated table in the source is not always feasible and adds complexity.

Answer

Use CALCULATE with a filter on the Products table

Answer

Create a calculated column in the Products table that sums the quantity

Answer

Create a summarized table in the source database and import it

Question 5

Which TWO of the following are valid reasons to use a calculated table instead of a calculated column in Power BI?

Accepted Answer

To create a summary table that is not present in the source.. Options B and D are correct. Calculated tables are used to create new tables based on DAX expressions, useful for creating a date table (B) or a summary table (D). Calculated columns are row-level and cannot produce new tables. Option A is not a reason; calculated columns can also use DAX. Option C is not a reason; both calculated tables and columns are recalculated on refresh.

Answer

To reduce model size by storing only aggregated data.

Answer

To create a column that depends on other columns in the same row.

Question 6

You are designing a Power BI semantic model for an e-commerce company. You have a fact table with OrderID, CustomerID, OrderDate, and SalesAmount. You also have a Customers table with CustomerID, CustomerName, and CustomerSegment. You need to ensure that filters on CustomerSegment propagate to the SalesAmount measure. What should you do?

Accepted Answer

Create a one-to-many relationship from Customers[CustomerID] to Sales[CustomerID].. Option A is correct because creating a relationship between the fact and dimension table based on CustomerID allows filters on CustomerSegment to propagate to the fact table. Option B is incorrect because merging tables is not necessary and may cause data duplication. Option C is not a Power BI feature. Option D is incorrect because a snowflake design is not required.

Answer

Use the LOOKUPVALUE function in a calculated column.

Answer

Merge the Customers and Sales tables into a single table in Power Query.

Answer

Create a snowflake schema by adding a separate Segment table.

Question 7

Which TWO of the following are valid DAX functions for modifying filter context within a measure? (Select two.)

Accepted Answer

FILTER. Options A and D are correct. CALCULATE is the primary function to modify filter context (A). FILTER is used as a table function inside CALCULATE (D). Option B is incorrect because SUM is an aggregation function, not filter modification. Option C is incorrect because ALL is a table function used to remove filters, but it is not a function that modifies filter context by itself; it is used inside CALCULATE. However, ALL is often used to clear filters, so it could be considered a filter modifier. The question expects CALCULATE and FILTER as direct answers.

Answer

VALUES

Answer

SUM

Answer

ALL

Question 8

Which TWO of the following are valid reasons to use a calculated table in Power BI instead of a table from the source?

Accepted Answer

To create a bridge table for many-to-many relationships. Options B and D are correct. Calculated tables can be used to create a date table or to create a bridge table for many-to-many relationships. Option A is wrong because calculated tables cannot be incremental refreshed. Option C is wrong because calculated tables are stored in the model, not to reduce storage. Option E is wrong because calculated tables are not for aggregating data at source; they are created in the model.

Answer

To aggregate data from the source before loading

Answer

To enable incremental data refresh

Answer

To reduce the overall storage size of the model

Question 9

Which TWO actions are valid for improving query performance in DirectQuery mode?

Accepted Answer

Create aggregated tables to pre-summarize data.. Option A is correct because reducing columns in the table reduces the data retrieved. Option C is correct because creating summarized tables can reduce data volume. Option B is wrong because disabling relationship enforcement can lead to incorrect results. Option D is wrong because calculated columns often degrade performance in DirectQuery. Option E is wrong because Import mode is not available in DirectQuery.

Answer

Disable relationship enforcement to speed up joins.

Answer

Convert the model to Import mode.

Answer

Use calculated columns in the fact table.

Question 10

You are designing a data model that will support self-service analytics. You have a Sales table with over 100 million rows. Which of the following modeling approaches would provide the best query performance while maintaining a user-friendly experience?

Accepted Answer

Design a star schema with a fact table and dimension tables. Star schema design separates facts and dimensions, optimizing query performance by reducing table scans and enabling efficient aggregations. Option C is correct. Option A is wrong because a single flat table with many columns can cause performance issues and is harder to maintain. Option B is wrong because a snowflake schema can increase query complexity and reduce performance due to additional joins. Option D is wrong because importing all tables into a single table duplicates data and loses normalization benefits.

Answer

Create a single flat table with all columns

Answer

Import all tables into a single table using Power Query merge

Answer

Use a snowflake schema with multiple levels of dimensions

Question 11

You have a Power BI report that shows sales by region. The data model contains a 'Sales' fact table and a 'Region' dimension table. When you filter by a specific region, the total sales for that region is correct, but the grand total shows all sales. What is the likely cause?

Accepted Answer

The relationship between Sales and Region is inactive. Option A is correct because if the relationship is inactive, filters won't propagate. Option B is wrong because measure calculation is not the issue. Option C is wrong because bidirectional would actually propagate. Option D is wrong because cross-filter direction is relevant.

Answer

The relationship is set to single cross-filter direction

Answer

The measure is using SUM instead of SUMX

Answer

The Region table is not marked as a dimension table

Question 12

You have a Power BI semantic model with a date table that spans from January 1, 2020 to December 31, 2025. You want to calculate year-to-date (YTD) sales for the current year. Which DAX formula should you use?

Accepted Answer

SalesYTD = TOTALYTD(SUM(Sales[Amount]), 'Date'[Date]). Option B is correct because TOTALYTD calculates year-to-date sales relative to the current context. Option A is wrong because it gives total sales without any time calculation. Option C is wrong because SAMEPERIODLASTYEAR compares to the prior year, not YTD. Option D is wrong because CALCULATE with DATESYTD is redundant; TOTALYTD is the standard function.

Answer

SalesYTD = SUM(Sales[Amount])

Answer

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

Answer

SalesYTD = CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR('Date'[Date]))

Question 13

You are building a star schema in Power BI. A fact table contains sales transactions with columns: OrderID, CustomerID, ProductID, Quantity, UnitPrice, Discount, and OrderDate. You need to create a dimension table for customers. Which columns should be included in the Customer dimension?

Accepted Answer

CustomerID, CustomerName, City, Region. Option B is correct because in a star schema, dimension tables should contain descriptive attributes (e.g., CustomerName, City, Region) and a unique key (CustomerID). Including foreign key columns like CustomerID from the fact table would violate normalization. Option A is wrong because including ProductID is irrelevant for customer dimension. Option C is wrong because OrderDate belongs to a date dimension. Option D is wrong because OrderID is a fact grain identifier.

Answer

CustomerID, CustomerName, ProductID

Answer

CustomerID, CustomerName, OrderID

Answer

CustomerID, CustomerName, OrderDate

Question 14

Which THREE of the following are best practices when designing a Power BI data model for performance?

Accepted Answer

Hide columns that are not needed in reports.. Options A, C, and D are correct. Star schema design (A) reduces complexity. Avoiding bi-directional cross-filtering (C) prevents performance degradation. Hiding unnecessary columns (D) reduces model size and improves clarity. Option B is incorrect because calculated columns are generally slower than measures for dynamic calculations. Option E is incorrect because using many-to-many relationships without bridge tables can cause ambiguity and poor performance.

Answer

Use many-to-many relationships directly without bridge tables.

Answer

Use calculated columns instead of measures for aggregations.

Question 15

Your organization uses Power BI with large datasets from Azure Synapse Analytics. You need to reduce model size and improve query performance. You decide to use aggregations. Which type of aggregation table is most appropriate for pre-aggregating data at the year and category level?

Accepted Answer

Table-based aggregation. Option B is correct because a table-based aggregation stores precomputed summaries in a separate table, commonly used for large datasets. Option A is not a standard aggregation type. Option C is incorrect because calculated tables are computed at refresh time and not pre-aggregated for performance. Option D is incorrect because measures are not stored.

Answer

Calculated table

Answer

Measure-based aggregation

Answer

In-memory aggregation

PL-300 Practice Test 19 — 15 Questions

Exhibit

PL-300 Practice Test 19 — 15 Questions

Exhibit