PL-300 Model the data Practice Test 6 — 15 Questions

Question 1

You have a Power BI model with a table 'Sales' and a table 'Date'. The relationship between them is many-to-one (Sales[OrderDate] -> Date[Date]). You notice that when you filter by Date[Year], some sales rows are not included. What is the most likely cause?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The relationship is inactive.. An inactive relationship does not automatically propagate filters between tables. Even though the relationship is defined, it must be explicitly activated using a DAX function like USERELATIONSHIP for filters to flow from Date to Sales. Without that, filtering by Date[Year] will not restrict Sales rows, causing some rows to appear missing if the user expects the filter to apply.

Answer

The relationship has Referential Integrity enforced.

Answer

The cross filter direction is set to Single.

Answer

The Date table has blank rows.

Question 2

You are reviewing a Power BI model definition in TMSL. The model has incremental refresh configured with two partitions. When the model refreshes on July 1, 2024, which data will be refreshed in Partition1?

Accepted Answer

All rows where OrderDate is between 2024-01-01 and 2024-04-01.. Option D is correct because in an incremental refresh setup, historical partitions are defined by static date ranges and are not re-queried on each refresh; a partition covering OrderDate between 2024-01-01 and 2024-04-01 is already materialized and will simply be retained as-is, so the July 1, 2024 refresh does not reload it with new rows. The refresh process only re-queries the partition whose range includes the current refresh window (typically the most recent period plus any newly created partitions), while completed past partitions remain unchanged. Option A is wrong because 'only new rows since last refresh' describes the incremental load of the active/recent partition, not a closed historical partition. Option B is wrong because the partition still contains its previously loaded data; it is not emptied just because its range is in the past. Option C is wrong because Power BI incremental refresh does not perform change tracking on modified rows; it partitions by date range and reloads whole partitions.

Answer

Only new rows added since last refresh.

Answer

No data, because the partition is in the past.

Answer

Only data modified since the last refresh.

Question 3

You are designing a Power BI data model that includes a Sales table and a Product table. The Product table contains a column 'Category' with values like 'Electronics', 'Clothing', etc. You need to create a measure that calculates the total sales amount for the 'Electronics' category only. Which DAX expression should you use?

Accepted Answer

CALCULATE(SUM(Sales[Amount]), Product[Category] = 'Electronics'). It uses CALCULATE to apply a filter condition directly on the Product[Category] column, which automatically performs a context transition along the existing relationship between Sales and Product. This efficiently computes the sum of Sales[Amount] only for rows where the related Product category is 'Electronics'.

Answer

SUM(Sales[Amount])

Answer

SUMX(FILTER(Sales, RELATED(Product[Category]) = 'Electronics'), Sales[Amount])

Answer

CALCULATE(SUM(Sales[Amount]), FILTER(Product, Product[Category] = 'Electronics'))

Question 4

You are examining a Power BI model definition. The Date table is generated via Power Query M code. The partition mode is 'import'. What will happen when the dataset refreshes after December 31, 2025?

Accepted Answer

The table will be refreshed with the same date range (2020-2025).. Since the partition mode is 'import' (not incremental), the entire table is replaced on each refresh. The M code generates dates from 2020-01-01 to 2025-12-31, so after 2025, no new dates will be added unless the code is updated. Option A is wrong because incremental refresh is not configured. Option B is wrong because the table is fully reloaded, not appended. Option D is wrong because the refresh will succeed, but no new dates beyond 2025 will appear.

Answer

The existing table will be appended with new rows.

Answer

The refresh will fail because EndDate is in the past.

Answer

New dates after 2025-12-31 will be added incrementally.

Question 5

You are modeling a many-to-many relationship between 'Students' and 'Courses' via a junction table 'Enrollments'. You need to create a measure that counts the number of students enrolled in at least one course. The relationship between Students and Enrollments is one-to-many, and between Courses and Enrollments is one-to-many. What DAX measure should you use?

Accepted Answer

DISTINCTCOUNT(Students[StudentID]). DISTINCTCOUNT(Students[StudentID]) counts the unique student IDs that appear in the filter context, which correctly answers 'how many students are enrolled in at least one course' because each student appears once regardless of how many enrollments they have. COUNTROWS(Enrollments) would count enrollment rows (a student in three courses counts three times), and COUNTA(Students[StudentID]) would count non-blank student IDs in the Students table, not those actually enrolled.

Answer

COUNTROWS(Enrollments)

Answer

COUNT(Courses[CourseID])

Answer

COUNTA(Students[StudentID])

Question 6

You need to create a hierarchy in Power BI that allows users to drill down from Year to Quarter to Month. Which of the following actions is required?

Accepted Answer

In the Fields pane, right-click a column and select 'Create hierarchy', then add child columns.. A hierarchy is created by selecting multiple columns in the same table and defining a parent-child relationship. Option A is incorrect because relationships are between tables, not within a hierarchy. Option B is incorrect because hierarchies can be created in the model view, not only in report view. Option D is incorrect because you cannot create a hierarchy in Power Query.

Answer

Create a relationship between the Year, Quarter, and Month columns.

Answer

Create the hierarchy in the report view by grouping fields.

Answer

Use Power Query to merge the columns into one.

Question 7

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.. The 'Filter Context' column in a DAX query represents the set of filters applied to the data at the time of evaluation. When a measure like COUNTROWS(Sales) is used, it counts all rows in the Sales table that are not filtered out by the current filter context. Option B is correct because COUNTROWS returns the total number of rows in the Sales table, regardless of product category, unless a filter on category is explicitly applied.

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 8

You have a Power BI model with a table 'Sales' and a table 'Date'. The relationship between them is many-to-one (Sales[OrderDate] -> Date[Date]). You notice that when you filter by Date[Year], some sales rows are not included. What is the most likely cause?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Calendar[Date])). Both options C and D are correct DAX expressions for calculating total sales for the previous month. PREVIOUSMONTH returns all dates in the previous month based on the current filter context, and when used with CALCULATE, it correctly filters the sales to the previous month. DATEADD with -1 month also shifts the date range back one month, achieving the same result. While PREVIOUSMONTH requires the calendar table to be marked as a date table, it is a standard and valid time intelligence function. Option A returns the same period last year, option B returns next month, so they are incorrect.

Answer

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

Answer

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

Question 9

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 expressions should you use? (Select all that apply.)

Accepted Answer

CALCULATE(SUM(Sales[SalesAmount]), DATESINPERIOD('Date'[Date], TODAY(), -30, DAY)). only. DATESINPERIOD with -30 DAY returns a contiguous period of 30 days, ending today. Option D includes 31 days because DATESBETWEEN is inclusive on both endpoints. Option A is month-to-date, not last 30 days. Option C filters directly on the fact table, ignores the date table, and also includes future dates if any, so it is not a valid/practice answer.

Answer

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

Answer

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

Answer

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

Question 10

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 C is correct because row-level security (RLS) defined on the 'Sales' dataset is enforced for any user who queries the dataset through a Viewer or Reshare role, so both user1 and user2 will have RLS filters applied to their query results. The Viewer role grants read-only access with RLS filtering, and the Reshare role also includes read access with RLS filtering while additionally allowing the user to share the dataset. Option A is incorrect because the Reshare role allows sharing but does not grant report-building (authoring) rights on the dataset. Option B is incorrect because adding measures requires write/build permissions on the dataset, which the Reshare role does not provide. Option D is incorrect because the Viewer role is read-only and cannot modify dataset structure via the XMLA endpoint.

Answer

user2 can share the dataset and can 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 11

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. The correct option is B, CROSSJOIN, because it produces the full Cartesian product of the Year and Product Category columns, guaranteeing every year-category combination appears even when there are no sales, which can then be left-joined to the sales totals. In DAX, CROSSJOIN is specifically designed to return all combinations of rows from two or more tables, so it directly addresses the missing rows for years or categories with no sales. ADDCOLUMNS only adds calculated columns to an existing table and does not generate missing combinations. SUMMARIZE groups existing data and therefore still omits combinations that have no underlying rows. EXPAND is not a DAX function for producing all combinations; it is not applicable here.

Answer

ADDCOLUMNS

Answer

SUMMARIZE

Answer

EXPAND

Question 12

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. Table-based aggregation stores precomputed summaries in a separate table, which aligns with the requirement for pre-aggregating data at the year and category level. Option A (Calculated table) is incorrect because calculated tables are computed at refresh time and do not serve as pre-aggregated storage for query performance. Option C (Measure-based aggregation) is incorrect because measures are computed on the fly and not stored as separate tables, so they do not pre-aggregate data. Option D (In-memory aggregation) is not a standard aggregation type in Power BI.

Answer

Calculated table

Answer

Measure-based aggregation

Answer

In-memory aggregation

Question 13

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'.. 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 14

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.. The correct answer is A: SAMEPERIODLASTYEAR does not handle leap years correctly for February 29. SAMEPERIODLASTYEAR shifts the current filter context back exactly one year by using DATEADD with -1 year, and when the current date is February 29 of a leap year, the corresponding date in the prior non-leap year does not exist, so the function returns a blank or mismatched period and the year-over-year growth for February is computed incorrectly. Option B is wrong because time-intelligence calculations like this require a measure evaluated in filter context, not a calculated column. Option C is wrong because the CurrentSales variable is a legitimate and useful intermediate step, not the cause of the error. Option D is wrong because DIVIDE handles a zero denominator by returning BLANK (or the alternate result) rather than raising an error, so it does not explain the leap-year issue.

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 15

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.. The retention pattern uses CALCULATE with a filter that intersects customers who made a purchase in the current period and previous period. Option B is incorrect because PREVIOUSCUSTOMER is not a DAX function. Option C is incorrect because DISTINCTCOUNT is a valid function, but using it over a concatenated key does not properly compare across two time periods; it only counts distinct customers in one context. Option D is incorrect because while a calculated column could be used, it is less flexible than a measure and does not adjust to filter context.

Answer

Use the PREVIOUSCUSTOMER function.

Answer

Use DISTINCTCOUNT over a concatenated key.

Answer

Add a calculated column to identify returning customers.