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Microsoft PL-300 Practice Test 12

Question 110

An analyst finds a large number of unexpected negative quantities in an order table. A colleague proposes: Delete every negative row without checking whether it represents an approved return. Which explanation BEST identifies the defect in that proposal?

  1. Blanket deletion may erase legitimate return transactions
  2. The suggested approach is safe merely because its product name is familiar.
  3. Out-of-range values can represent valid returns or data defects and require domain rules
  4. Fact duplicates may be valid line items and need different checks

Explanation

Correct Answer

A:

Blanket deletion may erase legitimate return transactions. This directly explains why the proposal 'Delete every negative row without checking whether it represents an approved return' should not be used.

Incorrect Answers

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Blanket deletion may erase legitimate return transactions.

C:

This is reasoning supporting the preferred solution 'Profile the quantity distribution and flag invalid or return-specific records for business review', but it does not directly name the defect in the proposed shortcut.

D:

This addresses a different case: A customer extract has duplicate records for the same customer key because of an accidental export join. It is not the specific defect in 'Delete every negative row without checking whether it represents an approved return'.

Question 111

An analyst finds a large number of unexpected negative quantities in an order table. After implementing Profile the quantity distribution and flag invalid or return-specific records for business review, which observation BEST demonstrates that the intended result is actually working?

  1. The team schedules a future check of whether Negative quantities are classified as valid returns or corrected errors, but has not observed a result.
  2. Negative quantities are classified as valid returns or corrected errors
  3. The report owner approves Profile the quantity distribution and flag invalid or return-specific records for business review without testing the resulting behavior.
  4. CustomerKey is unique and row counts agree with the trusted source

Explanation

Correct Answer

B:

The observation 'Negative quantities are classified as valid returns or corrected errors' directly tests the intended result. Out-of-range values can represent valid returns or data defects and require domain rules.

Incorrect Answers

A:

A future test is not yet observed operational evidence. The verification must establish: Negative quantities are classified as valid returns or corrected errors.

C:

Approval of a proposed design is not evidence of working behavior. The required observation is: Negative quantities are classified as valid returns or corrected errors.

D:

This belongs to a different case: A customer extract has duplicate records for the same customer key because of an accidental export join. It does not validate the current change.

Question 112

The original scenario was: An analyst finds a large number of unexpected negative quantities in an order table. The initial solution is already in place. Now this new requirement arises: The data owner defines a new returns transaction type. Which ADDITIONAL action BEST meets the changed condition?

  1. Profile the quantity distribution and flag invalid or return-specific records for business review
  2. Delete every negative row without checking whether it represents an approved return
  3. Map the new type into an explicit transaction-category column
  4. Negative quantities are classified as valid returns or corrected errors

Explanation

Correct Answer

C:

The changed requirement is 'The data owner defines a new returns transaction type'. The additional response is 'Map the new type into an explicit transaction-category column'.

Incorrect Answers

A:

This is the already implemented original solution: Profile the quantity distribution and flag invalid or return-specific records for business review. Out-of-range values can represent valid returns or data defects and require domain rules. It does not itself solve the new requirement.

B:

This remains unsuitable for the original situation: Blanket deletion may erase legitimate return transactions. It also does not meet the changed need.

D:

This observes the original approach but is not an additional action: Negative quantities are classified as valid returns or corrected errors.

Question 113

A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Normalize blank strings and nulls according to a consistent missing-data policy
  2. Identify and repair or exclude invalid key rows before relating the dimension
  3. Count only nulls and assume empty strings are valid email addresses
  4. Add a separate status column before consolidating missing values

Explanation

Correct Answer

A:

Empty text and null are distinct representations that may need unified handling. For the stated case, Normalize blank strings and nulls according to a consistent missing-data policy.

Incorrect Answers

B:

This addresses a separate source situation: A customer table contains null CustomerID values, yet CustomerID must identify a unique dimension member. It does not directly satisfy this case's priority. In the current question, this comparison is made against: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. Which approach BEST meets the stated Microsoft Power BI requirement?

C:

Empty strings may be unusable as contact addresses. The proposed shortcut 'Count only nulls and assume empty strings are valid email addresses' fails the documented need.

D:

This might be appropriate after a different requirement arises: A later requirement distinguishes not provided from deliberately withheld. It is not the best initial response to the stated case.

Question 114

A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. A colleague proposes: Count only nulls and assume empty strings are valid email addresses. Which explanation BEST identifies the defect in that proposal?

  1. One shared replacement key collapses unrelated customers together
  2. The suggested approach is safe merely because its product name is familiar.
  3. Empty text and null are distinct representations that may need unified handling
  4. Empty strings may be unusable as contact addresses

Explanation

Correct Answer

D:

Empty strings may be unusable as contact addresses. This directly explains why the proposal 'Count only nulls and assume empty strings are valid email addresses' should not be used.

Incorrect Answers

A:

This addresses a different case: A customer table contains null CustomerID values, yet CustomerID must identify a unique dimension member. It is not the specific defect in 'Count only nulls and assume empty strings are valid email addresses'.

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Empty strings may be unusable as contact addresses.

C:

This is reasoning supporting the preferred solution 'Normalize blank strings and nulls according to a consistent missing-data policy', but it does not directly name the defect in the proposed shortcut.

Question 115

A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. After implementing Normalize blank strings and nulls according to a consistent missing-data policy, which observation BEST demonstrates that the intended result is actually working?

  1. The team schedules a future check of whether The missing-email rate includes both formerly blank and null source entries, but has not observed a result.
  2. The report owner approves Normalize blank strings and nulls according to a consistent missing-data policy without testing the resulting behavior.
  3. CustomerID is nonblank and unique under the agreed quality rule
  4. The missing-email rate includes both formerly blank and null source entries

Explanation

Correct Answer

D:

The observation 'The missing-email rate includes both formerly blank and null source entries' directly tests the intended result. Empty text and null are distinct representations that may need unified handling.

Incorrect Answers

A:

A future test is not yet observed operational evidence. The verification must establish: The missing-email rate includes both formerly blank and null source entries.

B:

Approval of a proposed design is not evidence of working behavior. The required observation is: The missing-email rate includes both formerly blank and null source entries.

C:

This belongs to a different case: A customer table contains null CustomerID values, yet CustomerID must identify a unique dimension member. It does not validate the current change. In the current question, this comparison is made against: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. After implementing Normalize blank strings and nulls according to a consistent missing-data policy, which observation BEST demonstrates that the intended result is actually working?

Question 116

The original scenario was: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. The initial solution is already in place. Now this new requirement arises: A later requirement distinguishes not provided from deliberately withheld. Which ADDITIONAL action BEST meets the changed condition?

  1. Add a separate status column before consolidating missing values
  2. The missing-email rate includes both formerly blank and null source entries
  3. Normalize blank strings and nulls according to a consistent missing-data policy
  4. Count only nulls and assume empty strings are valid email addresses

Explanation

Correct Answer

A:

The changed requirement is 'A later requirement distinguishes not provided from deliberately withheld'. The additional response is 'Add a separate status column before consolidating missing values'.

Incorrect Answers

B:

This observes the original approach but is not an additional action: The missing-email rate includes both formerly blank and null source entries.

C:

This is the already implemented original solution: Normalize blank strings and nulls according to a consistent missing-data policy. Empty text and null are distinct representations that may need unified handling. It does not itself solve the new requirement.

D:

This remains unsuitable for the original situation: Empty strings may be unusable as contact addresses. It also does not meet the changed need.

Question 117

One supplier CSV occasionally introduces a text note into a Whole Number identifier column. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Use error detection and schema-aware conversion for the affected identifier
  2. Turn off all model refresh without examining the changed input
  3. Normalize blank strings and nulls according to a consistent missing-data policy
  4. Use Text identifiers with an appropriate stable business-key scheme

Explanation

Correct Answer

A:

Strict type conversion can create cell errors when source values drift. For the stated case, Use error detection and schema-aware conversion for the affected identifier.

Incorrect Answers

B:

Suppressing refresh does not explain or correct the schema exception. The proposed shortcut 'Turn off all model refresh without examining the changed input' fails the documented need.

C:

This addresses a separate source situation: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. It does not directly satisfy this case's priority. In the current question, this comparison is made against: One supplier CSV occasionally introduces a text note into a Whole Number identifier column. Which approach BEST meets the stated Microsoft Power BI requirement?

D:

This might be appropriate after a different requirement arises: The supplier switches to alphanumeric identifiers permanently. It is not the best initial response to the stated case.

Question 118

One supplier CSV occasionally introduces a text note into a Whole Number identifier column. A colleague proposes: Turn off all model refresh without examining the changed input. Which explanation BEST identifies the defect in that proposal?

  1. Empty strings may be unusable as contact addresses
  2. The suggested approach is safe merely because its product name is familiar.
  3. Suppressing refresh does not explain or correct the schema exception
  4. Strict type conversion can create cell errors when source values drift

Explanation

Correct Answer

C:

Suppressing refresh does not explain or correct the schema exception. This directly explains why the proposal 'Turn off all model refresh without examining the changed input' should not be used.

Incorrect Answers

A:

This addresses a different case: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. It is not the specific defect in 'Turn off all model refresh without examining the changed input'.

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Suppressing refresh does not explain or correct the schema exception.

D:

This is reasoning supporting the preferred solution 'Use error detection and schema-aware conversion for the affected identifier', but it does not directly name the defect in the proposed shortcut.

Question 119

One supplier CSV occasionally introduces a text note into a Whole Number identifier column. After implementing Use error detection and schema-aware conversion for the affected identifier, which observation BEST demonstrates that the intended result is actually working?

  1. The team schedules a future check of whether Conversion failures are isolated and refreshed valid rows remain traceable, but has not observed a result.
  2. The missing-email rate includes both formerly blank and null source entries
  3. Conversion failures are isolated and refreshed valid rows remain traceable
  4. The report owner approves Use error detection and schema-aware conversion for the affected identifier without testing the resulting behavior.

Explanation

Correct Answer

C:

The observation 'Conversion failures are isolated and refreshed valid rows remain traceable' directly tests the intended result. Strict type conversion can create cell errors when source values drift.

Incorrect Answers

A:

A future test is not yet observed operational evidence. The verification must establish: Conversion failures are isolated and refreshed valid rows remain traceable.

B:

This belongs to a different case: A source table has both empty strings and nulls in Email, and the analyst needs one missing-value definition. It does not validate the current change. In the current question, this comparison is made against: One supplier CSV occasionally introduces a text note into a Whole Number identifier column. After implementing Use error detection and schema-aware conversion for the affected identifier, which observation BEST demonstrates that the intended result is actually working?

D:

Approval of a proposed design is not evidence of working behavior. The required observation is: Conversion failures are isolated and refreshed valid rows remain traceable.

Question 120

The original scenario was: One supplier CSV occasionally introduces a text note into a Whole Number identifier column. The initial solution is already in place. Now this new requirement arises: The supplier switches to alphanumeric identifiers permanently. Which ADDITIONAL action BEST meets the changed condition?

  1. Conversion failures are isolated and refreshed valid rows remain traceable
  2. Use Text identifiers with an appropriate stable business-key scheme
  3. Use error detection and schema-aware conversion for the affected identifier
  4. Turn off all model refresh without examining the changed input

Explanation

Correct Answer

B:

The changed requirement is 'The supplier switches to alphanumeric identifiers permanently'. The additional response is 'Use Text identifiers with an appropriate stable business-key scheme'.

Incorrect Answers

A:

This observes the original approach but is not an additional action: Conversion failures are isolated and refreshed valid rows remain traceable.

C:

This is the already implemented original solution: Use error detection and schema-aware conversion for the affected identifier. Strict type conversion can create cell errors when source values drift. It does not itself solve the new requirement.

D:

This remains unsuitable for the original situation: Suppressing refresh does not explain or correct the schema exception. It also does not meet the changed need.

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