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Microsoft PL-300 Bundle

Exam Code: PL-300

Exam Name Microsoft Power BI Data Analyst

Certification Provider: Microsoft

Corresponding Certification: Microsoft Certified: Power BI Data Analyst Associate

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Microsoft PL-300 Practice Test 17

Question 160

A maintenance table has rows (TaskID,Status): (T31,Open), (T31,Closed), (T32,Closed), (T33,Open), (T34,Closed). A measure CALCULATE(DISTINCTCOUNT(Fact[TaskID]), Fact[Status] = "Closed") runs with no other filters. What result should it return?

  1. 5 because every row is counted regardless of repeated TaskID
  2. 4 because all IDs are included despite the Closed filter
  3. 3 distinct closed-task IDs: T31, T32 and T34
  4. 2 because the Open row for T31 excludes T31 from all other rows

Explanation

Correct Answer

C:

The filter keeps closed rows T31, T32 and T34; their distinct count is three even though T31 also has an Open row outside the selected subset.

Incorrect Answers

A:

Five is row count without de-duplicating and without the filter.

B:

The unfiltered count of four IDs includes open-only T33.

D:

A task with at least one Closed row remains in the selected Closed rows.

Question 161

A wholesaler closes its fiscal year in March. On a report axis, April should be period 1, May period 2, and March period 12, while the labels remain month names. A MonthNumber column currently assigns January=1. What will meet the fiscal order?

  1. Sort by calendar MonthNumber 1 through 12
  2. Apply a numeric filter limiting the visual to the first fiscal quarter
  3. Create FiscalMonthIndex = MOD(MonthNumber + 8, 12) + 1 and sort month name by that index
  4. Keep sorting month names alphabetically

Explanation

Correct Answer

C:

MOD shifts April (4) to 1 and March (3) to 12, providing one stable ordering key for the fiscal display.

Incorrect Answers

A:

Calendar month numbers make January period 1 and place April fourth, which is not the requested April-first fiscal year.

B:

Filtering changes which months appear, not their underlying relative fiscal sequence.

D:

Alphabetical order is unrelated to the April–March fiscal sequence.

Question 162

A publishing team asks a Power BI workspace Member to invite a new Viewer for a limited read-only assignment. No existing workspace access needs to be removed or changed. Under the normal workspace roles, what can the Member do?

  1. Delete the workspace to reset its access matrix
  2. Add the new Viewer because Members can add users with lower permissions, while removal of existing users remains an Admin operation
  3. Remove an existing Admin from the workspace without escalation
  4. Disable RLS for all consumers so workspace invitation becomes unnecessary

Explanation

Correct Answer

B:

Members can add users with lower privileges, but cannot unilaterally remove existing roles or change existing user assignments.

Incorrect Answers

A:

Deleting the workspace destroys content and does not implement a scoped invite.

C:

Removal and changes to existing user access are Admin operations, not general Member capabilities.

D:

Row security is independent of workspace invitation and should not be disabled to solve access management.

Question 163

A streaming service stores viewing events at individual EventID grain. Its Market names sometimes change, but an event should keep its assigned stable MarketID for consistent reporting. How should the model handle that descriptive text?

  1. Use MarketName text as a transaction identifier because names never change
  2. Move every EventID into the Markets dimension and aggregate away session events
  3. Duplicate all viewing-event facts every time a market display name changes
  4. Keep MarketID on each event row and relate it to a distinct Markets lookup that contains the current approved descriptive label

Explanation

Correct Answer

D:

A stable foreign key on the event and a distinct market dimension separate label management from event facts without multiplying events.

Incorrect Answers

A:

Mutable business names are unreliable as row identifiers.

B:

Moving event IDs to the dimension destroys the intended per-event grain.

C:

Duplicating facts inflates viewing totals and is not needed for label changes.

Question 164

A finance matrix has Year and Quarter in Rows and CostCenter in Columns. A controller wants to inspect quarters under each year while retaining the year group. Which visual action provides this?

  1. Switch the matrix to a single total Card
  2. Use only a chart title containing the quarter names
  3. Change source dates to free-text month descriptions
  4. Expand the Year row hierarchy down one level instead of replacing it with just Quarter

Explanation

Correct Answer

D:

Matrix expand retains parent Year while exposing the grouped Quarter rows.

Incorrect Answers

A:

A Card removes the hierarchy and quarter comparisons.

B:

Titles cannot expose nested data groups.

C:

Text conversion is unnecessary and can disrupt chronological grouping.

Question 165

An airport maintenance feed records one row per aircraft task status change, including EventID, AirportID, Status and WorkHours. The Airports name and city repeat in many status-change rows. A star-shaped model must support counts of individual events and airport slicers. Which preparation is appropriate?

  1. Keep the status-change fact at EventID grain with AirportID as a foreign key and create a unique AirportID dimension for airport attributes
  2. Aggregate away all status changes to one row per airport before reporting event counts
  3. Move each unique EventID into the Airports dimension as a descriptive column
  4. Create one separate fact table for each airport name

Explanation

Correct Answer

A:

The event is the declared fact grain; deduplicated airport attributes belong on the dimension, preserving event counts and slicers.

Incorrect Answers

B:

Aggregating first loses the source transition records needed for event analysis.

C:

EventID identifies a fact event and is not an airport lookup attribute.

D:

Per-airport fact tables complicate totals and undermine shared modeling.

Question 166

A logistics warehouse has two distinct reasons for missing warehouse-location data: records genuinely assigned to an official Unknown location category and records whose source Location value is NULL because an upstream feed omitted it. The first is a valid classification. How should its quality report handle them?

  1. Replace every legitimate Unknown location with null to make both categories identical
  2. Delete all rows with either null or Unknown so the report has no unresolved locations
  3. Assign the current headquarters location automatically to every missing source row
  4. Maintain a separate missing-source indicator for nulls while preserving the valid Unknown category and report the two counts separately

Explanation

Correct Answer

D:

An explicitly classified Unknown location is not identical to absent data; separate categories avoid fabricating locations or hiding data-quality issues.

Incorrect Answers

A:

Collapsing them loses the distinction between a documented business classification and missing input.

B:

Deleting legitimate work orders distorts operational population and obscures source errors.

C:

Defaulting to headquarters creates false location assignments.

Question 167

An aviation services group needs a governance review of who can build reports from a shared maintenance tasks semantic model. Which permission is the most relevant to inventory and audit?

  1. Only dashboard theme permissions
  2. Only bookmarks saved by viewers
  3. Only column format strings
  4. Build access to the semantic model and its inherited permission paths

Explanation

Correct Answer

D:

Build enables derived-report creation and must be governed for certified shared maintenance tasks models.

Incorrect Answers

A:

Theme settings do not grant semantic model reuse.

B:

Bookmarks capture states and are not model access permissions.

C:

Column formatting does not authorize creating derived model content.

Question 168

A Fabric semantic model was extended through automation with a new Delta table. DAX queries fail because the table has not been framed. Which action addresses this specific condition?

  1. Refresh the semantic model to frame the newly added table before querying
  2. Delete the existing Date relationships to bypass metadata
  3. Replace its table label with an Excel filename
  4. Add a tooltip page to force query metadata loading

Explanation

Correct Answer

A:

Framing updates the Direct Lake model’s view of table files and is required after programmatically adding tables.

Incorrect Answers

B:

Relationship deletion does not frame the new table.

C:

Renaming does not update Delta framing metadata.

D:

Tooltips are report presentation and cannot frame a semantic-model table.

Question 169

A three-row fact table has Region and ProfitRate: East 20%, East 40%, West 90%. A measure uses CALCULATE(AVERAGEX(Fact, Fact[ProfitRate]), Fact[Region] = "East") with no other filters. What value does it return?

  1. 50%, the unfiltered average of all three rows
  2. 60%, the mean of the East 30% and West 90% subgroup averages
  3. 90%, because the West row has the highest individual rate
  4. 30%

Explanation

Correct Answer

D:

CALCULATE constrains the row context available to the iterator to the East subset; AVERAGEX then averages 20% and 40% to 30%.

Incorrect Answers

A:

The West 90% row is excluded by the explicit East filter.

B:

Combining the two region averages would reintroduce West despite the filter.

C:

The maximum West rate does not override an East-only measure.

Question 170

A grid operator considers rolling minute readings into daily totals to shrink its model. Compliance must still identify a 30-minute voltage spike. What constraint should govern the change?

  1. Discard the original timestamps because daily totals always identify half-hour peaks
  2. Sum the daily values twice to mimic the missing variation
  3. Replace the time field with day-of-week text and assume the spike remains recoverable
  4. Retain access to an intraday detail grain for spike investigations even if daily aggregate tables serve general dashboards

Explanation

Correct Answer

D:

Daily aggregates lose the temporal information needed to identify a short spike unless fine-grain data is kept elsewhere.

Incorrect Answers

A:

Summation removes the within-day shape and cannot locate the specific interval.

B:

Double-counting aggregates does not reconstruct the true minute observations.

C:

Day names have less precision than dates/times and cannot identify a 30-minute episode.