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Microsoft PL-300 Practice Test 44

Question 430

Power Query transforms a SQL source in ways that unexpectedly pull millions of rows into the local engine. A colleague proposes: Add nonfoldable custom operations before a selective SQL filter without checking impact. Which explanation BEST identifies the defect in that proposal?

  1. The suggested approach is safe merely because its product name is familiar.
  2. Extra bidirectional filters do not replace a valid aggregation design
  3. Folding pushes supported transformations to the source database
  4. Early nonfoldable steps can force unnecessary local processing

Explanation

Correct Answer

D:

Early nonfoldable steps can force unnecessary local processing. This directly explains why the proposal 'Add nonfoldable custom operations before a selective SQL filter without checking impact' should not be used.

Incorrect Answers

A:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Early nonfoldable steps can force unnecessary local processing.

B:

This addresses a different case: A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. It is not the specific defect in 'Add nonfoldable custom operations before a selective SQL filter without checking impact'.

C:

This is reasoning supporting the preferred solution 'Check query folding and move compatible filters earlier in the query', but it does not directly name the defect in the proposed shortcut.

Question 431

Power Query transforms a SQL source in ways that unexpectedly pull millions of rows into the local engine. After implementing Check query folding and move compatible filters earlier in the query, which observation BEST demonstrates that the intended result is actually working?

  1. The team schedules a future check of whether Source query tracing confirms a selective SQL WHERE clause, but has not observed a result.
  2. The report owner approves Check query folding and move compatible filters earlier in the query without testing the resulting behavior.
  3. Source query tracing confirms a selective SQL WHERE clause
  4. Common monthly visuals use the aggregation and return correct totals

Explanation

Correct Answer

C:

The observation 'Source query tracing confirms a selective SQL WHERE clause' directly tests the intended result. Folding pushes supported transformations to the source database.

Incorrect Answers

A:

A future test is not yet observed operational evidence. The verification must establish: Source query tracing confirms a selective SQL WHERE clause.

B:

Approval of a proposed design is not evidence of working behavior. The required observation is: Source query tracing confirms a selective SQL WHERE clause.

D:

This belongs to a different case: A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. It does not validate the current change.

Question 432

The original scenario was: Power Query transforms a SQL source in ways that unexpectedly pull millions of rows into the local engine. The initial solution is already in place. Now this new requirement arises: A custom transformation cannot be expressed in native SQL. Which ADDITIONAL action BEST meets the changed condition?

  1. Stage a filtered subset before applying the nonfoldable step
  2. Check query folding and move compatible filters earlier in the query
  3. Source query tracing confirms a selective SQL WHERE clause
  4. Add nonfoldable custom operations before a selective SQL filter without checking impact

Explanation

Correct Answer

A:

The changed requirement is 'A custom transformation cannot be expressed in native SQL'. The additional response is 'Stage a filtered subset before applying the nonfoldable step'.

Incorrect Answers

B:

This is the already implemented original solution: Check query folding and move compatible filters earlier in the query. Folding pushes supported transformations to the source database. It does not itself solve the new requirement.

C:

This observes the original approach but is not an additional action: Source query tracing confirms a selective SQL WHERE clause.

D:

This remains unsuitable for the original situation: Early nonfoldable steps can force unnecessary local processing. It also does not meet the changed need.

Question 433

A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Introduce an appropriate import aggregation table mapped to the detailed source
  2. Increase cross-filter direction on every relationship to reduce data scan cost
  3. Route the detail request to the appropriate underlying detail table
  4. Use Performance Analyzer to capture and compare visual query durations

Explanation

Correct Answer

A:

Aggregations can answer summary queries without scanning full detail every time. For the stated case, Introduce an appropriate import aggregation table mapped to the detailed source.

Incorrect Answers

B:

Extra bidirectional filters do not replace a valid aggregation design. The proposed shortcut 'Increase cross-filter direction on every relationship to reduce data scan cost' fails the documented need.

C:

This might be appropriate after a different requirement arises: Users request detailed drillthrough for one order. It is not the best initial response to the stated case.

D:

This addresses a separate source situation: A report loads slowly and the analyst must identify which specific visual is responsible. It does not directly satisfy this case's priority. In the current question, this comparison is made against: A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. Which approach BEST meets the stated Microsoft Power BI requirement?

Question 434

A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. A colleague proposes: Increase cross-filter direction on every relationship to reduce data scan cost. Which explanation BEST identifies the defect in that proposal?

  1. Guesswork can remove useful visuals without locating the bottleneck
  2. The suggested approach is safe merely because its product name is familiar.
  3. Aggregations can answer summary queries without scanning full detail every time
  4. Extra bidirectional filters do not replace a valid aggregation design

Explanation

Correct Answer

D:

Extra bidirectional filters do not replace a valid aggregation design. This directly explains why the proposal 'Increase cross-filter direction on every relationship to reduce data scan cost' should not be used.

Incorrect Answers

A:

This addresses a different case: A report loads slowly and the analyst must identify which specific visual is responsible. It is not the specific defect in 'Increase cross-filter direction on every relationship to reduce data scan cost'.

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Extra bidirectional filters do not replace a valid aggregation design.

C:

This is reasoning supporting the preferred solution 'Introduce an appropriate import aggregation table mapped to the detailed source', but it does not directly name the defect in the proposed shortcut.

Question 435

A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. After implementing Introduce an appropriate import aggregation table mapped to the detailed source, which observation BEST demonstrates that the intended result is actually working?

  1. Captured timings identify the costly visual and a targeted change reduces duration
  2. Common monthly visuals use the aggregation and return correct totals
  3. The team schedules a future check of whether Common monthly visuals use the aggregation and return correct totals, but has not observed a result.
  4. The report owner approves Introduce an appropriate import aggregation table mapped to the detailed source without testing the resulting behavior.

Explanation

Correct Answer

B:

The observation 'Common monthly visuals use the aggregation and return correct totals' directly tests the intended result. Aggregations can answer summary queries without scanning full detail every time.

Incorrect Answers

A:

This belongs to a different case: A report loads slowly and the analyst must identify which specific visual is responsible. It does not validate the current change. In the current question, this comparison is made against: A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. After implementing Introduce an appropriate import aggregation table mapped to the detailed source, which observation BEST demonstrates that the intended result is actually working?

C:

A future test is not yet observed operational evidence. The verification must establish: Common monthly visuals use the aggregation and return correct totals.

D:

Approval of a proposed design is not evidence of working behavior. The required observation is: Common monthly visuals use the aggregation and return correct totals.

Question 436

The original scenario was: A large DirectQuery model needs monthly sales totals much more frequently than individual line-level detail. The initial solution is already in place. Now this new requirement arises: Users request detailed drillthrough for one order. Which ADDITIONAL action BEST meets the changed condition?

  1. Common monthly visuals use the aggregation and return correct totals
  2. Introduce an appropriate import aggregation table mapped to the detailed source
  3. Increase cross-filter direction on every relationship to reduce data scan cost
  4. Route the detail request to the appropriate underlying detail table

Explanation

Correct Answer

D:

The changed requirement is 'Users request detailed drillthrough for one order'. The additional response is 'Route the detail request to the appropriate underlying detail table'.

Incorrect Answers

A:

This observes the original approach but is not an additional action: Common monthly visuals use the aggregation and return correct totals.

B:

This is the already implemented original solution: Introduce an appropriate import aggregation table mapped to the detailed source. Aggregations can answer summary queries without scanning full detail every time. It does not itself solve the new requirement.

C:

This remains unsuitable for the original situation: Extra bidirectional filters do not replace a valid aggregation design. It also does not meet the changed need.

Question 437

A desktop model auto-creates many hidden date tables for every datetime field. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Disable unnecessary automatic date/time tables and use a conformed Date dimension
  2. Add a role-playing date table or inactive relationship strategy
  3. Create another auto date hierarchy for each transaction timestamp
  4. Filter unnecessary source rows before import and validate query folding

Explanation

Correct Answer

A:

Auto date/time hidden tables may add size and fragment calendar logic. For the stated case, Disable unnecessary automatic date/time tables and use a conformed Date dimension.

Incorrect Answers

B:

This might be appropriate after a different requirement arises: A role requires an independent shipping date analysis. It is not the best initial response to the stated case.

C:

More hidden date tables are not a cohesive shared calendar. The proposed shortcut 'Create another auto date hierarchy for each transaction timestamp' fails the documented need.

D:

This addresses a separate source situation: A Sales table contains a billion historical rows but the business only analyzes recent months. It does not directly satisfy this case's priority.

Question 438

A desktop model auto-creates many hidden date tables for every datetime field. A colleague proposes: Create another auto date hierarchy for each transaction timestamp. Which explanation BEST identifies the defect in that proposal?

  1. The suggested approach is safe merely because its product name is familiar.
  2. Auto date/time hidden tables may add size and fragment calendar logic
  3. More hidden date tables are not a cohesive shared calendar
  4. Visual filtering does not reduce semantic-model ingestion cost

Explanation

Correct Answer

C:

More hidden date tables are not a cohesive shared calendar. This directly explains why the proposal 'Create another auto date hierarchy for each transaction timestamp' should not be used.

Incorrect Answers

A:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: More hidden date tables are not a cohesive shared calendar.

B:

This is reasoning supporting the preferred solution 'Disable unnecessary automatic date/time tables and use a conformed Date dimension', but it does not directly name the defect in the proposed shortcut.

D:

This addresses a different case: A Sales table contains a billion historical rows but the business only analyzes recent months. It is not the specific defect in 'Create another auto date hierarchy for each transaction timestamp'.

Question 439

A desktop model auto-creates many hidden date tables for every datetime field. After implementing Disable unnecessary automatic date/time tables and use a conformed Date dimension, which observation BEST demonstrates that the intended result is actually working?

  1. The report owner approves Disable unnecessary automatic date/time tables and use a conformed Date dimension without testing the resulting behavior.
  2. The model uses one marked Date table and has fewer hidden date structures
  3. The source-side query excludes old periods and the model shrinks
  4. The team schedules a future check of whether The model uses one marked Date table and has fewer hidden date structures, but has not observed a result.

Explanation

Correct Answer

B:

The observation 'The model uses one marked Date table and has fewer hidden date structures' directly tests the intended result. Auto date/time hidden tables may add size and fragment calendar logic.

Incorrect Answers

A:

Approval of a proposed design is not evidence of working behavior. The required observation is: The model uses one marked Date table and has fewer hidden date structures.

C:

This belongs to a different case: A Sales table contains a billion historical rows but the business only analyzes recent months. It does not validate the current change.

D:

A future test is not yet observed operational evidence. The verification must establish: The model uses one marked Date table and has fewer hidden date structures.

Question 440

The original scenario was: A desktop model auto-creates many hidden date tables for every datetime field. The initial solution is already in place. Now this new requirement arises: A role requires an independent shipping date analysis. Which ADDITIONAL action BEST meets the changed condition?

  1. Create another auto date hierarchy for each transaction timestamp
  2. Disable unnecessary automatic date/time tables and use a conformed Date dimension
  3. Add a role-playing date table or inactive relationship strategy
  4. The model uses one marked Date table and has fewer hidden date structures

Explanation

Correct Answer

C:

The changed requirement is 'A role requires an independent shipping date analysis'. The additional response is 'Add a role-playing date table or inactive relationship strategy'.

Incorrect Answers

A:

This remains unsuitable for the original situation: More hidden date tables are not a cohesive shared calendar. It also does not meet the changed need.

B:

This is the already implemented original solution: Disable unnecessary automatic date/time tables and use a conformed Date dimension. Auto date/time hidden tables may add size and fragment calendar logic. It does not itself solve the new requirement.

D:

This observes the original approach but is not an additional action: The model uses one marked Date table and has fewer hidden date structures.

Microsoft Power BI Data Analyst (PL-300) Practice Tests