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PL-300 Premium File: 413 Questions & Answers

Last Update: Oct 30, 2026

PL-300 Training Course: 266 Video Lectures

PL-300 PDF Study Guide: 452 Pages

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Microsoft PL-300 Practice Test 35

Question 340

A Matrix includes country totals and individual store rows; the measure should change logic at store level. What is the MOST appropriate Power BI design decision?

  1. Use SELECTEDVALUE(Product[Category],"All Categories").
  2. Use ISINSCOPE(Store[StoreID]) to detect row hierarchy level.
  3. Use SELECTEDVALUE(Status[State]) with explicit handling for multi-value context.
  4. Check ISINSCOPE for Product, Category and Department levels in descending specificity.

Explanation

Correct Answer

B:

ISINSCOPE identifies whether the specified hierarchy column defines current grouping level, supporting hierarchy-aware store-level metric.

Incorrect Answers

A:

SELECTEDVALUE provides a clear alternate for none or multiple category selections. It would address context-aware report category label, not hierarchy-aware store-level metric.

C:

Single-value selection guards against arbitrary scalar picks in ambiguous contexts. It may suit safe selected status in conditional measure, not hierarchy-aware store-level metric.

D:

ISINSCOPE supports level-specific logic for report hierarchies. It is useful for dynamic hierarchy-level detection, not for hierarchy-aware store-level metric.

Question 341

A calculated column on Sales uses a measure expecting product filters and returns an unexpected per-row result. Which configuration should the team choose?

  1. Use a compatible iterator or alternate relationship-aware measure pattern.
  2. Account for CALCULATE context transition from current row to filter context.
  3. Inspect context transition and relationship propagation for that column expression.
  4. Use SUMX with an explicit per-row commission expression and appropriate filters.

Explanation

Correct Answer

C:

Row-context-to-filter-context behavior can change how measures evaluate during column calculation, supporting debug calculated-column measure behavior.

Incorrect Answers

A:

RELATED expects row context from an appropriate relationship traversal. It is useful for resolving missing row context for related lookup, not for debug calculated-column measure behavior.

B:

CALCULATE can translate row context into filter context for aggregation evaluation. Its scope is correct aggregation inside a row iterator, not debug calculated-column measure behavior.

D:

Row iteration evaluates business rules at transaction grain. It would address sum per-transaction commission correctly, not debug calculated-column measure behavior.

Question 342

A required mapping of values to departments is not supplied as a separate source but can be derived from a governed table. What is the MOST appropriate Power BI design decision?

  1. Replace it with a distinct lightweight category dimension.
  2. Construct an explicitly validated month-end calendar table expression.
  3. Build a CALENDAR or CALENDARAUTO-based date table with governed boundaries.
  4. Define a calculated table using DISTINCT or SUMMARIZE where appropriate.

Explanation

Correct Answer

D:

Calculated tables can materialize unique grouping values from existing model records, supporting derive an internal grouping table.

Incorrect Answers

A:

Small unique dimension tables avoid unnecessary duplicate fact storage. It would address reduce redundant calculated table size, not derive an internal grouping table.

B:

Calculated tables can materialize needed date-grain rows under defined calendar logic. That targets dedicated month-end date dimension, not derive an internal grouping table.

C:

DAX date-table expressions materialize date rows for modeling. It may suit generate a complete calendar table, not derive an internal grouping table.

Question 343

An analytics report requires unique buying CustomerIDs during the selected period. What is the best method for this analysis requirement?

  1. Define Revenue = SUM(Sales[NetAmount]) as a measure.
  2. Define Transactions = COUNTROWS(Sales).
  3. Define Customers = DISTINCTCOUNT(Sales[CustomerID]).
  4. Define Avg Satisfaction = AVERAGE(Feedback[Score]).

Explanation

Correct Answer

C:

DISTINCTCOUNT avoids counting multiple transactions for the same customer as separate buyers, supporting unique purchasing customer count.

Incorrect Answers

A:

SUM aggregates numeric fact values within the current filter context. It is useful for additive filtered revenue metric, not for unique purchasing customer count.

B:

COUNTROWS counts records in the filtered fact table rather than distinct identifiers. Its scope is filtered transaction event count, not unique purchasing customer count.

D:

AVERAGE calculates the mean of eligible numeric values in filter context. It would address context-sensitive average satisfaction, not unique purchasing customer count.

Question 344

A measure needs the selected year's revenue but also must retain a more restrictive Product filter already present. Which implementation best addresses this scenario?

  1. Calculate the denominator with only Product filtering removed.
  2. Use CALCULATE([Revenue],Sales[Channel] = "Online").
  3. Use CALCULATE([Revenue],REMOVEFILTERS(Product[Category])).
  4. Use CALCULATE with KEEPFILTERS for the additional Product condition.

Explanation

Correct Answer

D:

KEEPFILTERS intersects a new condition with existing filters rather than overwriting them, supporting intersect selected product conditions.

Incorrect Answers

A:

Controlled filter removal retains intended region context for the baseline. It would address regional product share versus regional total, not intersect selected product conditions.

B:

CALCULATE modifies filter context for the enclosed expression. That targets revenue restricted to online channel, not intersect selected product conditions.

C:

REMOVEFILTERS clears only the specified category filter while other compatible filters remain. It may suit product-category-independent revenue, not intersect selected product conditions.

Question 345

A measure uses SUMX over order lines to multiply Quantity and Price before summing. What is the best method for this analysis requirement?

  1. Use SUMX(Sales,Sales[Quantity] * Sales[Price]).
  2. Use RELATED(Product[Category]) in Sales calculated column context.
  3. Use a row-context calculated column Sales[Quantity] * Sales[UnitPrice].
  4. Write a DAX measure evaluated under filter context.

Explanation

Correct Answer

A:

SUMX iterates rows, evaluates the expression per row, and sums the results, supporting sum a row-by-row calculated sales amount.

Incorrect Answers

B:

RELATED retrieves a single corresponding attribute from the relationship's one side. Its scope is retrieve dimension category for each sale row, not sum a row-by-row calculated sales amount.

C:

Calculated columns evaluate each row's fields at model processing. That is meant for per-line extended price, not sum a row-by-row calculated sales amount.

D:

Measures respond to active report filters rather than storing one static per-row value. It would address responsive report aggregation, not sum a row-by-row calculated sales amount.

Question 346

A sales page needs revenue accumulated within the current month up to the selected date. Which implementation best addresses this scenario?

  1. Use TOTALYTD with the appropriate fiscal year-end parameter or a fiscal calendar.
  2. Use TOTALMTD([Revenue],'Date'[Date]) over the date dimension.
  3. Use TOTALQTD([Revenue],'Date'[Date]) with a valid date dimension.
  4. Use TOTALYTD([Revenue],'Date'[Date]) with a proper calendar.

Explanation

Correct Answer

B:

Month-to-date resets the accumulation at each month boundary, supporting selected month-to-date total.

Incorrect Answers

A:

Fiscal YTD changes the accumulation boundary from the calendar year to the fiscal year. It would address fiscal year-to-date financial amount, not selected month-to-date total.

C:

Quarter-to-date calculations aggregate within the current quarter context. It may suit partial-quarter cumulative revenue, not selected month-to-date total.

D:

TOTALYTD aggregates a measure from year start to the current date context. It is useful for calendar year-to-date revenue, not for selected month-to-date total.

Question 347

A rolling four-week sales figure should cover the last 28 days ending at the report date. What is the best method for this analysis requirement?

  1. Use CALCULATE([Revenue],SAMEPERIODLASTYEAR('Date'[Date])).
  2. Use CALCULATE([Revenue],PREVIOUSMONTH('Date'[Date])).
  3. Use CALCULATE([Revenue],DATESINPERIOD('Date'[Date],MAX('Date'[Date]),-28,DAY)).
  4. Define a variance measure as [Revenue] - [Revenue PY] using a valid prior-year measure.

Explanation

Correct Answer

C:

DATESINPERIOD defines a relative date window evaluated by CALCULATE, supporting trailing 28-day revenue.

Incorrect Answers

A:

SAMEPERIODLASTYEAR shifts the date filter to a comparable prior-year interval. It is useful for prior-year matched-period sales, not for trailing 28-day revenue.

B:

PREVIOUSMONTH replaces the current date set with the previous month interval. Its scope is previous-month sales comparison, not trailing 28-day revenue.

D:

Variance measures subtract comparable quantities after matching time contexts. It would address absolute year-over-year revenue change, not trailing 28-day revenue.

Question 348

A headcount dashboard should display monthly employee count but not sum monthly headcounts into an annual total. Which implementation best addresses this scenario?

  1. Use an additive SUM of cash-receipt transactions for the date interval.
  2. Evaluate the balance measure on the last eligible date of each period.
  3. Use a LASTNONBLANK-based date context with the stock balance expression.
  4. Calculate headcount as of the selected period end.

Explanation

Correct Answer

D:

Headcount is semi-additive across organizational units but not across time, supporting headcount at reporting period end.

Incorrect Answers

A:

Cash receipts are period flows and should aggregate through time. It would address quarterly inflow rather than closing balance, not headcount at reporting period end.

B:

A closing balance is a point-in-time stock rather than daily additive flow. That targets period-ending account balance, not headcount at reporting period end.

C:

Last nonblank date patterns find the final available inventory snapshot. It may suit most recent available inventory state, not headcount at reporting period end.

Question 349

An average price KPI must weight order amounts by units sold rather than averaging transaction-level prices. What is the best method for this analysis requirement?

  1. Use DIVIDE([Revenue],[Units]) after summing both measures.
  2. Use DIVIDE([Revenue],CALCULATE([Revenue],REMOVEFILTERS(Product))).
  3. Use DIVIDE([GrossMargin],[Revenue],BLANK()).
  4. Use DIVIDE([Valid Cases],[Tested Cases],0) when zero is the approved fallback.

Explanation

Correct Answer

A:

Ratio of totals gives a quantity-weighted price under filter context, supporting weighted realized price per unit.

Incorrect Answers

B:

Removing only Product from denominator provides total over selected time. Its scope is product share of selected-period overall revenue, not weighted realized price per unit.

C:

DIVIDE handles zero or blank denominators with a defined alternative result. That is meant for safe gross margin percentage, not weighted realized price per unit.

D:

DIVIDE provides a controlled fallback rather than unsafe direct division. It would address controlled compliance completion ratio, not weighted realized price per unit.

Question 350

A Customer table includes inactive customers and a KPI must count only Active rows. Which implementation best addresses this scenario?

  1. Use COUNTROWS(DeliveryLines) in the required context.
  2. Use CALCULATE(COUNTROWS(Customer),Customer[Status] = "Active").
  3. Calculate DISTINCTCOUNT(UserActivity[UserID]) for the whole month context.
  4. Use DISTINCTCOUNT(Sales[CustomerID]) under month filter context.

Explanation

Correct Answer

B:

The status filter constrains the rows included in the count, supporting active customer master count.

Incorrect Answers

A:

Row counting preserves multiple lines per shipment as separate events. It would address number of delivery line events, not active customer master count.

C:

Repeated users must be deduplicated across the combined period. It may suit avoid duplicated cross-day distinct users, not active customer master count.

D:

DISTINCTCOUNT counts unique IDs in the active date filter. It is useful for unique monthly buyers, not for active customer master count.


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