PL-300 Model the data Practice Test 11 — 15 Questions

Question 1

You are analyzing a DAX query. What is the purpose of the 'Filter Context' column in the result?

Accepted Answer

It returns the total number of sales rows regardless of product category.. Option D is correct. CALCULATE(COUNTROWS('Sales'), ALL('Product')) counts all sales rows ignoring any filter on the Product table. This is useful to compare category-level sales against total sales. Option A is wrong because it does not count distinct products. Option B is wrong because it does not filter by current year. Option C is wrong because it counts sales rows, not product rows.

Answer

It returns the total sales for the current year, ignoring category.

Answer

It returns the number of product categories in the current context.

Answer

It counts the number of distinct products in the current filter context.

Question 2

You have a Power BI model with a table 'Sales' and a separate 'Calendar' table. The relationship between Sales[OrderDate] and Calendar[Date] is active. You need to create a measure that calculates the total sales for the previous month relative to the current filter context. Which DAX expression should you use?

Accepted Answer

CALCULATE(SUM(Sales[Amount]), DATEADD(Calendar[Date], -1, MONTH)). Option C is correct. CALCULATE with DATEADD shifting by -1 month returns the same period last month. Option A uses PREVIOUSMONTH which is equivalent but requires a continuous date range; DATEADD is more flexible. Option B returns dates in the next month. Option D returns dates in the same month of previous year.

Answer

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

Answer

CALCULATE(SUM(Sales[Amount]), NEXTMONTH(Calendar[Date]))

Answer

CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Calendar[Date]))

Question 3

You need to create a relationship between two tables in Power BI. Table A has a column 'ProductID' with unique values. Table B has a column 'ProductID' with duplicate values. Which relationship cardinality should you choose?

Accepted Answer

One-to-many (Table A to Table B). Option A is correct. Since Table A has unique values and Table B has duplicates, the relationship is one-to-many (Table A to Table B). Option B is wrong because many-to-one would imply Table A has duplicates. Option C is wrong because one-to-one requires uniqueness on both sides. Option D is wrong because many-to-many requires a junction table.

Answer

Many-to-one (Table A to Table B)

Answer

One-to-one

Answer

Many-to-many

Question 4

You have a Power BI semantic model that imports sales data from Azure SQL Database. The model includes a date table and a fact table with a column 'SalesAmount'. You need to create a measure that calculates the total sales amount only for the last 30 days relative to the report date. Which DAX expression should you use?

Accepted Answer

CALCULATE(SUM(Sales[SalesAmount]), DATESBETWEEN('Date'[Date], TODAY()-30, TODAY())). Option B is correct because TOTALMTD is a time intelligence function that calculates month-to-date, not last 30 days. Option A uses DATESBETWEEN with a fixed range of 30 days from today, which matches the requirement. Option C returns the first 30 days of the current month. Option D sums all sales in the last 30 days but does not filter by date.

Answer

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

Answer

CALCULATE(SUM(Sales[SalesAmount]), DATESINPERIOD('Date'[Date], TODAY(), -30, DAY))

Answer

SUMX(FILTER(Sales, Sales[Date] >= TODAY()-30), Sales[SalesAmount])

Question 5

Refer to the exhibit. You are managing a Power BI workspace and applying dataset permissions via the XMLA endpoint. The JSON policy shows permissions for two users on the 'Sales' dataset. user1 has Viewer role, user2 has Reshare role. The dataset has row-level security (RLS) defined. Which statement is true about the permissions?

Accepted Answer

Both users will have RLS applied when querying the dataset.. Option A is correct because RLS is enforced for both Viewer and Reshare roles. Option B is incorrect because Reshare allows sharing but not necessarily modifying reports. Option C is incorrect because Viewer cannot modify the dataset. Option D is incorrect because Reshare does not allow editing the dataset.

Answer

user2 can share the dataset with others but cannot build reports.

Answer

user2 can add new measures to the dataset using the XMLA endpoint.

Answer

user1 can modify the dataset structure through the XMLA endpoint.

Question 6

You are modeling a fact table that contains sales transactions with columns: OrderDate, ShipDate, SalesAmount, CustomerKey. You need to create a relationship to a date table. The date table has a single Date column. Which relationship should you create for the most accurate time-based analysis?

Accepted Answer

Create an active relationship from OrderDate to Date and an inactive relationship from ShipDate to Date.. Option C is correct because you should create an active relationship from OrderDate to Date for standard reporting, and an inactive relationship from ShipDate to Date that can be activated using USERELATIONSHIP. Option A would have multiple active relationships causing ambiguity. Option B is not recommended as it omits an important date. Option D is incorrect because you can have multiple relationships, one active and others inactive.

Answer

Create a single relationship from OrderDate to Date and ignore ShipDate.

Answer

Create two active relationships: OrderDate to Date and ShipDate to Date.

Answer

Create only one relationship from ShipDate to Date.

Question 7

Refer to the exhibit. You are using DAX Studio to profile a Power BI semantic model. The query above returns a table with sales totals by year and product category. However, you notice that the results do not include rows for years or categories with no sales. Which DAX function should you use to ensure all combinations of year and category appear, even with blank sales?

Accepted Answer

CROSSJOIN. Option D is correct because CROSSJOIN generates all combinations of the columns, then you can left join with the sales table. Option A is for cross-tabulation. Option B is an older function that may not handle blanks well. Option C is not a valid DAX function.

Answer

ADDCOLUMNS

Answer

SUMMARIZE

Answer

EXPAND

Question 8

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 9

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

Question 10

Refer to the exhibit. You have defined row-level security (RLS) in a Power BI semantic model using Role-level security. The JSON shows three rules for the 'Sales' and 'Targets' tables. The user 'john@contoso.com' belongs to this role. John's manager column in the Sales table has the value 'john@contoso.com'. What data will John see when he queries the model?

Accepted Answer

Sales rows where Region is 'West' and Manager is 'john@contoso.com'; Targets rows where Region is 'West'.. Option A is correct because RLS rules are combined with AND logic. John will see only Sales rows where Region is 'West' AND Manager is 'john@contoso.com'. For Targets, only rows with Region 'West'. Option B is incorrect because OR is not used. Option C is incorrect because both rules on Sales apply. Option D is incorrect because all rules apply.

Answer

All Sales and Targets data because John is a manager.

Answer

Sales rows where Region is 'West' OR Manager is 'john@contoso.com'; Targets rows where Region is 'West'.

Answer

Only Sales rows where Manager is 'john@contoso.com'; no Targets restriction.

Question 11

You are building a Power BI semantic model that includes a Date table. Which of the following is a best practice for creating a Date table?

Accepted Answer

Mark the date table as a date table in Power BI Desktop.. Option D is correct because marking a table as a date table enables time intelligence functions. Option A is incorrect because the date table should have a contiguous range of dates. Option B is incorrect because using CALENDARAUTO can produce unpredictable ranges. Option C is incorrect because the date table should not have a relationship to every fact table; only one active relationship per fact table is needed.

Answer

Create relationships from the date table to every fact table column that contains dates.

Answer

Use the CALENDARAUTO function to automatically generate dates.

Answer

Use a date table that includes only dates that exist in the fact tables.

Question 12

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 13

You have a Power BI semantic model with a fact table containing sales data at the transaction level. You need to create a measure that calculates the number of distinct customers who made a purchase in the current period and also made a purchase in the previous period. Which DAX pattern should you use?

Accepted Answer

Use CALCULATE with a filter that intersects customers in both periods.. Option A is correct because the semi-additive pattern using CALCULATE and FILTER with an EARLIER-like approach is typical for retention. Option B is incorrect because DISTINCTCOUNT is not a standard function. Option C is incorrect because a calculated column is less flexible. Option D is not a standard pattern.

Answer

Use the PREVIOUSCUSTOMER function.

Answer

Use DISTINCTCOUNT over a concatenated key.

Answer

Add a calculated column to identify returning customers.

Question 14

Which TWO of the following are valid reasons to create a separate date table in a Power BI semantic model? (Select two.)

Accepted Answer

To enable time intelligence functions like TOTALYTD.. Options A and C are correct. A date table is required for time intelligence functions (A) and for filtering by date attributes not present in the fact table (C). Option B is incorrect because relationships are one-to-many. Option D is incorrect because multiple active relationships cause ambiguity. Option E is incorrect because measures can be calculated without a date table, but time intelligence functions need it.

Answer

To calculate measures that require date arithmetic.

Answer

To create many-to-many relationships between fact tables.

Answer

To allow multiple active relationships from the same fact table to the date table.

Question 15

Which TWO of the following are best practices when designing star schemas in Power BI? (Select two.)

Accepted Answer

Store numeric measures in fact tables.. Option A is correct because fact tables in a star schema are designed to store quantitative, numeric measures (e.g., sales amount, quantity) that can be aggregated. This aligns with the star schema principle of separating measures (facts) from descriptive context (dimensions), enabling efficient compression and fast aggregations in Power BI's VertiPaq engine.

Answer

Use calculated columns in fact tables for row-level security.

Answer

Include many columns in fact tables for filtering.

Answer

Normalize dimension tables to reduce redundancy.

PL-300 Model the data Practice Test 11 — 15 Questions

Exhibit

PL-300 Model the data Practice Test 11 — 15 Questions

Exhibit