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Microsoft PL-300 Practice Test 22

Question 210

An inventory file lists multiple stock locations per product and analysts want the number of locations. A colleague proposes: Remove duplicates on ProductID before counting locations. Which explanation BEST identifies the defect in that proposal?

  1. Deduplication at product grain loses valid location rows
  2. Group By can aggregate a source at a product-level grain
  3. Sorting another source does not transform XML nodes
  4. The suggested approach is safe merely because its product name is familiar.

Explanation

Correct Answer

A:

Deduplication at product grain loses valid location rows. This directly explains why the proposal 'Remove duplicates on ProductID before counting locations' should not be used.

Incorrect Answers

B:

This is reasoning supporting the preferred solution 'Group by ProductID and calculate a distinct location count', but it does not directly name the defect in the proposed shortcut.

C:

This addresses a different case: An order-source XML file has repeated LineItem nodes that must become fact rows. It is not the specific defect in 'Remove duplicates on ProductID before counting locations'.

D:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Deduplication at product grain loses valid location rows.

Question 211

An inventory file lists multiple stock locations per product and analysts want the number of locations. After implementing Group by ProductID and calculate a distinct location count, which observation BEST demonstrates that the intended result is actually working?

  1. The team schedules a future check of whether Counts match an independent distinct product-location tally, but has not observed a result.
  2. The report owner approves Group by ProductID and calculate a distinct location count without testing the resulting behavior.
  3. Every valid LineItem becomes a row linked to its parent OrderID
  4. Counts match an independent distinct product-location tally

Explanation

Correct Answer

D:

The observation 'Counts match an independent distinct product-location tally' directly tests the intended result. Group By can aggregate a source at a product-level grain.

Incorrect Answers

A:

A future test is not yet observed operational evidence. The verification must establish: Counts match an independent distinct product-location tally.

B:

Approval of a proposed design is not evidence of working behavior. The required observation is: Counts match an independent distinct product-location tally.

C:

This belongs to a different case: An order-source XML file has repeated LineItem nodes that must become fact rows. It does not validate the current change.

Question 212

The original scenario was: An inventory file lists multiple stock locations per product and analysts want the number of locations. The initial solution is already in place. Now this new requirement arises: Analysts later want total stock units per product as well. Which ADDITIONAL action BEST meets the changed condition?

  1. Add a Sum aggregation for UnitsInStock in the grouped output
  2. Group by ProductID and calculate a distinct location count
  3. Counts match an independent distinct product-location tally
  4. Remove duplicates on ProductID before counting locations

Explanation

Correct Answer

A:

The changed requirement is 'Analysts later want total stock units per product as well'. The additional response is 'Add a Sum aggregation for UnitsInStock in the grouped output'.

Incorrect Answers

B:

This is the already implemented original solution: Group by ProductID and calculate a distinct location count. Group By can aggregate a source at a product-level grain. It does not itself solve the new requirement.

C:

This observes the original approach but is not an additional action: Counts match an independent distinct product-location tally.

D:

This remains unsuitable for the original situation: Deduplication at product grain loses valid location rows. It also does not meet the changed need.

Question 213

A Power Query dataset needs Column A as headers and has one junk metadata row at the top. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Remove the non-data top row and promote the correct first data row to headers
  2. Transpose the table repeatedly until headers look correct
  3. Convert JSON lists and records to tables and expand the required fields
  4. Update the number of rows removed before promoting headers

Explanation

Correct Answer

A:

Promote Headers uses a row as column names, so the correct row must be first. For the stated case, Remove the non-data top row and promote the correct first data row to headers.

Incorrect Answers

B:

Transposition is not a substitute for removing metadata rows. The proposed shortcut 'Transpose the table repeatedly until headers look correct' fails the documented need.

C:

This addresses a separate source situation: A web API returns JSON with nested Customer and Addresses records that must become flat columns. It does not directly satisfy this case's priority.

D:

This might be appropriate after a different requirement arises: A revised export includes three metadata rows instead of one. It is not the best initial response to the stated case.

Question 214

A Power Query dataset needs Column A as headers and has one junk metadata row at the top. A colleague proposes: Transpose the table repeatedly until headers look correct. Which explanation BEST identifies the defect in that proposal?

  1. Transposition is not a substitute for removing metadata rows
  2. The suggested approach is safe merely because its product name is familiar.
  3. Renaming alone leaves the record data nested
  4. Promote Headers uses a row as column names, so the correct row must be first

Explanation

Correct Answer

A:

Transposition is not a substitute for removing metadata rows. This directly explains why the proposal 'Transpose the table repeatedly until headers look correct' should not be used.

Incorrect Answers

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: Transposition is not a substitute for removing metadata rows.

C:

This addresses a different case: A web API returns JSON with nested Customer and Addresses records that must become flat columns. It is not the specific defect in 'Transpose the table repeatedly until headers look correct'.

D:

This is reasoning supporting the preferred solution 'Remove the non-data top row and promote the correct first data row to headers', but it does not directly name the defect in the proposed shortcut.

Question 215

A Power Query dataset needs Column A as headers and has one junk metadata row at the top. After implementing Remove the non-data top row and promote the correct first data row to headers, which observation BEST demonstrates that the intended result is actually working?

  1. Customer and address properties appear as typed columns after expansion
  2. Headers show business field names and the junk row is absent
  3. The team schedules a future check of whether Headers show business field names and the junk row is absent, but has not observed a result.
  4. The report owner approves Remove the non-data top row and promote the correct first data row to headers without testing the resulting behavior.

Explanation

Correct Answer

B:

The observation 'Headers show business field names and the junk row is absent' directly tests the intended result. Promote Headers uses a row as column names, so the correct row must be first.

Incorrect Answers

A:

This belongs to a different case: A web API returns JSON with nested Customer and Addresses records that must become flat columns. It does not validate the current change.

C:

A future test is not yet observed operational evidence. The verification must establish: Headers show business field names and the junk row is absent.

D:

Approval of a proposed design is not evidence of working behavior. The required observation is: Headers show business field names and the junk row is absent.

Question 216

The original scenario was: A Power Query dataset needs Column A as headers and has one junk metadata row at the top. The initial solution is already in place. Now this new requirement arises: A revised export includes three metadata rows instead of one. Which ADDITIONAL action BEST meets the changed condition?

  1. Headers show business field names and the junk row is absent
  2. Transpose the table repeatedly until headers look correct
  3. Update the number of rows removed before promoting headers
  4. Remove the non-data top row and promote the correct first data row to headers

Explanation

Correct Answer

C:

The changed requirement is 'A revised export includes three metadata rows instead of one'. The additional response is 'Update the number of rows removed before promoting headers'.

Incorrect Answers

A:

This observes the original approach but is not an additional action: Headers show business field names and the junk row is absent.

B:

This remains unsuitable for the original situation: Transposition is not a substitute for removing metadata rows. It also does not meet the changed need.

D:

This is the already implemented original solution: Remove the non-data top row and promote the correct first data row to headers. Promote Headers uses a row as column names, so the correct row must be first. It does not itself solve the new requirement.

Question 217

A transactions table includes a currency field stored as text such as 1,234.56 USD. Which approach BEST meets the stated Microsoft Power BI requirement?

  1. Parse amount and currency into appropriate numeric and text columns
  2. Apply culture-aware numeric parsing per input source
  3. Change the entire combined field to Whole Number without parsing its suffix
  4. Parse the YYYYMMDD string into a true Date value

Explanation

Correct Answer

A:

Currency codes and amounts should be independently typed for aggregation. For the stated case, Parse amount and currency into appropriate numeric and text columns.

Incorrect Answers

B:

This might be appropriate after a different requirement arises: Some values use comma decimals instead of period decimals. It is not the best initial response to the stated case.

C:

A currency suffix prevents numeric conversion and loses currency meaning. The proposed shortcut 'Change the entire combined field to Whole Number without parsing its suffix' fails the documented need.

D:

This addresses a separate source situation: A report source stores the number 20261231 as text and wants proper daily date filtering. It does not directly satisfy this case's priority. In the current question, this comparison is made against: A transactions table includes a currency field stored as text such as 1,234.56 USD. Which approach BEST meets the stated Microsoft Power BI requirement?

Question 218

A transactions table includes a currency field stored as text such as 1,234.56 USD. A colleague proposes: Change the entire combined field to Whole Number without parsing its suffix. Which explanation BEST identifies the defect in that proposal?

  1. A currency suffix prevents numeric conversion and loses currency meaning
  2. The suggested approach is safe merely because its product name is familiar.
  3. Currency codes and amounts should be independently typed for aggregation
  4. Formatting text does not guarantee a typed calendar value

Explanation

Correct Answer

A:

A currency suffix prevents numeric conversion and loses currency meaning. This directly explains why the proposal 'Change the entire combined field to Whole Number without parsing its suffix' should not be used.

Incorrect Answers

B:

Product familiarity is not evidence of suitability. The actual defect in this proposal is: A currency suffix prevents numeric conversion and loses currency meaning.

C:

This is reasoning supporting the preferred solution 'Parse amount and currency into appropriate numeric and text columns', but it does not directly name the defect in the proposed shortcut.

D:

This addresses a different case: A report source stores the number 20261231 as text and wants proper daily date filtering. It is not the specific defect in 'Change the entire combined field to Whole Number without parsing its suffix'.

Question 219

A transactions table includes a currency field stored as text such as 1,234.56 USD. After implementing Parse amount and currency into appropriate numeric and text columns, which observation BEST demonstrates that the intended result is actually working?

  1. Amount sums correctly and the original ISO currency code is retained
  2. 31 December 2026 is interpreted as a real date with correct sorting
  3. The team schedules a future check of whether Amount sums correctly and the original ISO currency code is retained, but has not observed a result.
  4. The report owner approves Parse amount and currency into appropriate numeric and text columns without testing the resulting behavior.

Explanation

Correct Answer

A:

The observation 'Amount sums correctly and the original ISO currency code is retained' directly tests the intended result. Currency codes and amounts should be independently typed for aggregation.

Incorrect Answers

B:

This belongs to a different case: A report source stores the number 20261231 as text and wants proper daily date filtering. It does not validate the current change. In the current question, this comparison is made against: A transactions table includes a currency field stored as text such as 1,234.56 USD. After implementing Parse amount and currency into appropriate numeric and text columns, 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: Amount sums correctly and the original ISO currency code is retained.

D:

Approval of a proposed design is not evidence of working behavior. The required observation is: Amount sums correctly and the original ISO currency code is retained.

Question 220

The original scenario was: A transactions table includes a currency field stored as text such as 1,234.56 USD. The initial solution is already in place. Now this new requirement arises: Some values use comma decimals instead of period decimals. Which ADDITIONAL action BEST meets the changed condition?

  1. Amount sums correctly and the original ISO currency code is retained
  2. Parse amount and currency into appropriate numeric and text columns
  3. Change the entire combined field to Whole Number without parsing its suffix
  4. Apply culture-aware numeric parsing per input source

Explanation

Correct Answer

D:

The changed requirement is 'Some values use comma decimals instead of period decimals'. The additional response is 'Apply culture-aware numeric parsing per input source'.

Incorrect Answers

A:

This observes the original approach but is not an additional action: Amount sums correctly and the original ISO currency code is retained.

B:

This is the already implemented original solution: Parse amount and currency into appropriate numeric and text columns. Currency codes and amounts should be independently typed for aggregation. It does not itself solve the new requirement.

C:

This remains unsuitable for the original situation: A currency suffix prevents numeric conversion and loses currency meaning. It also does not meet the changed need.

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