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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 15

Question 140

A sales fact joins to a slowly changing Customer dimension with multiple historical rows per customer. What is needed?

  1. Run an anti join to identify fact foreign keys with no dimension match.
  2. Build a stable unique business or surrogate key for the dimension.
  3. Use the correct version-specific surrogate dimension key.
  4. Convert both relationship key columns to compatible data types.

Explanation

Correct Answer

C:

Use the correct version-specific surrogate dimension key. Type-2 dimensions require keys identifying the historical attribute version.

Incorrect Answers

A:

Run an anti join to identify fact foreign keys with no dimension match. This solves “contains ProductID values missing from the Product dimension”; the stated issue is “Customer dimension with multiple historical rows per customer”.

B:

Names are nonunique and may change, making weak relationship keys. The deciding difference is “no unique ID is present, resulting in collisions” versus “Customer dimension with multiple historical rows per customer”.

D:

Related key columns need compatible representations to match values. That is a different operating condition from “Customer dimension with multiple historical rows per customer”: “Sales but Text in Customers, and relationships fail”.

Question 141

An intermediate query exists only to prepare columns used by two downstream queries. What should happen to its model load?

  1. Turn off Enable Load for the staging-only query.
  2. Keep it as a reusable function invoked by source queries.
  3. Enable Load for the final semantic table query.
  4. Disable loading or remove the unnecessary debug query after confirming dependencies.

Explanation

Correct Answer

A:

Turn off Enable Load for the staging-only query. Staging transformations remain reusable without an extra semantic-model table.

Incorrect Answers

B:

Parameterized functions transform inputs without requiring their own loaded table. It serves “but should not create a standalone fact table”, not “to prepare columns used by two downstream queries”.

C:

Load-enabled queries create tables accessible to the model. The present requirement is “to prepare columns used by two downstream queries”; “report modeling and must appear in Model view” is a distinct situation.

D:

Unused loaded tables waste memory and refresh resources. That matters for “loads 50 million rows” rather than the condition “to prepare columns used by two downstream queries”.

Question 142

A query is useful for report modeling and must appear in Model view. Which setting is required?

  1. Turn off Enable Load for the staging-only query.
  2. Enable Load for the final semantic table query.
  3. Review Include in Report Refresh carefully before disabling it.
  4. Disable loading or remove the unnecessary debug query after confirming dependencies.

Explanation

Correct Answer

B:

Enable Load for the final semantic table query. Load-enabled queries create tables accessible to the model.

Incorrect Answers

A:

Staging transformations remain reusable without an extra semantic-model table. That matters for “to prepare columns used by two downstream queries” rather than the condition “report modeling and must appear in Model view”.

C:

Can excluding from report refresh be used without considering staleness?. This solves “from report refresh be used without considering staleness”; the stated issue is “report modeling and must appear in Model view”.

D:

Unused loaded tables waste memory and refresh resources. The deciding difference is “loads 50 million rows” versus “report modeling and must appear in Model view”.

Question 143

A query refresh is expensive but the dataset needs the table in memory. Can excluding from report refresh be used without considering staleness?

  1. Review Include in Report Refresh carefully before disabling it.
  2. Disable loading or remove the unnecessary debug query after confirming dependencies.
  3. Turn off Enable Load for the staging-only query.
  4. Enable Load for the final semantic table query.

Explanation

Correct Answer

A:

Review Include in Report Refresh carefully before disabling it. Can excluding from report refresh be used without considering staleness?.

Incorrect Answers

B:

Unused loaded tables waste memory and refresh resources. Its application is “loads 50 million rows”, not the need “from report refresh be used without considering staleness”.

C:

Staging transformations remain reusable without an extra semantic-model table. That is a different operating condition from “from report refresh be used without considering staleness”: “to prepare columns used by two downstream queries”.

D:

Load-enabled queries create tables accessible to the model. It serves “report modeling and must appear in Model view”, not “from report refresh be used without considering staleness”.

Question 144

A Power Query function uses parameters and returns a table but should not create a standalone fact table. What role does it play?

  1. Keep it as a reusable function invoked by source queries.
  2. Review Include in Report Refresh carefully before disabling it.
  3. Turn off Enable Load for the staging-only query.
  4. Enable Load for the final semantic table query.

Explanation

Correct Answer

A:

Keep it as a reusable function invoked by source queries. Parameterized functions transform inputs without requiring their own loaded table.

Incorrect Answers

B:

Can excluding from report refresh be used without considering staleness?. The present requirement is “but should not create a standalone fact table”; “from report refresh be used without considering staleness” is a distinct situation.

C:

Staging transformations remain reusable without an extra semantic-model table. That matters for “to prepare columns used by two downstream queries” rather than the condition “but should not create a standalone fact table”.

D:

Load-enabled queries create tables accessible to the model. The boundary it addresses is “report modeling and must appear in Model view”, while this case concerns “but should not create a standalone fact table”.

Question 145

A model contains an unused debug query that loads 50 million rows. What should be done?

  1. Keep it as a reusable function invoked by source queries.
  2. Enable Load for the final semantic table query.
  3. Turn off Enable Load for the staging-only query.
  4. Disable loading or remove the unnecessary debug query after confirming dependencies.

Explanation

Correct Answer

D:

Disable loading or remove the unnecessary debug query after confirming dependencies. Unused loaded tables waste memory and refresh resources.

Incorrect Answers

A:

Parameterized functions transform inputs without requiring their own loaded table. The boundary it addresses is “but should not create a standalone fact table”, while this case concerns “loads 50 million rows”.

B:

Load-enabled queries create tables accessible to the model. This solves “report modeling and must appear in Model view”; the stated issue is “loads 50 million rows”.

C:

Staging transformations remain reusable without an extra semantic-model table. The deciding difference is “to prepare columns used by two downstream queries” versus “loads 50 million rows”.

Question 146

A Power Query custom column must branch according to a null-safe status field. Which language is appropriate?

  1. Write a Power Query M conditional expression using if then else.
  2. Filter rows in Power Query before loading the table.
  3. Preserve the dependency order of Power Query transformation steps.
  4. Expand the list to new rows and then expand its records.

Explanation

Correct Answer

A:

Write a Power Query M conditional expression using if then else. M expressions define row-level transformations at data preparation time.

Incorrect Answers

B:

A row filter can reduce the imported dataset and may fold to the source. That is a different operating condition from “must branch according to a null-safe status field”: “keeps rows with Quantity > 0”.

C:

M evaluation composes named steps whose downstream references require upstream results. It serves “Steps in which later steps reference earlier names”, not “must branch according to a null-safe status field”.

D:

List expansion creates one row per nested element before its fields are expanded. The present requirement is “must branch according to a null-safe status field”; “each array element to become a separate record” is a distinct situation.

Question 147

A report needs an M step that keeps rows with Quantity > 0. Which function family is relevant?

  1. Add a custom column using an M arithmetic expression.
  2. Expand the list to new rows and then expand its records.
  3. Write a Power Query M conditional expression using if then else.
  4. Filter rows in Power Query before loading the table.

Explanation

Correct Answer

D:

Filter rows in Power Query before loading the table. A row filter can reduce the imported dataset and may fold to the source.

Incorrect Answers

A:

A Power Query custom column computes a new value for every input row during refresh. The present requirement is “keeps rows with Quantity > 0”; “field should multiply it by 1.07 during load” is a distinct situation.

B:

List expansion creates one row per nested element before its fields are expanded. That matters for “each array element to become a separate record” rather than the condition “keeps rows with Quantity > 0”.

C:

M expressions define row-level transformations at data preparation time. The boundary it addresses is “must branch according to a null-safe status field”, while this case concerns “keeps rows with Quantity > 0”.

Question 148

A table has an Amount column, and a new AmountTaxed field should multiply it by 1.07 during load. Which operation fits?

  1. Filter rows in Power Query before loading the table.
  2. Write a Power Query M conditional expression using if then else.
  3. Expand the list to new rows and then expand its records.
  4. Add a custom column using an M arithmetic expression.

Explanation

Correct Answer

D:

Add a custom column using an M arithmetic expression. A Power Query custom column computes a new value for every input row during refresh.

Incorrect Answers

A:

A row filter can reduce the imported dataset and may fold to the source. This solves “keeps rows with Quantity > 0”; the stated issue is “field should multiply it by 1.07 during load”.

B:

M expressions define row-level transformations at data preparation time. The deciding difference is “must branch according to a null-safe status field” versus “field should multiply it by 1.07 during load”.

C:

List expansion creates one row per nested element before its fields are expanded. Its application is “each array element to become a separate record”, not the need “field should multiply it by 1.07 during load”.

Question 149

An M query shows a list of Applied Steps in which later steps reference earlier names. What does ordering imply?

  1. Filter rows in Power Query before loading the table.
  2. Preserve the dependency order of Power Query transformation steps.
  3. Expand the list to new rows and then expand its records.
  4. Write a Power Query M conditional expression using if then else.

Explanation

Correct Answer

B:

Preserve the dependency order of Power Query transformation steps. M evaluation composes named steps whose downstream references require upstream results.

Incorrect Answers

A:

A row filter can reduce the imported dataset and may fold to the source. That is a different operating condition from “Steps in which later steps reference earlier names”: “keeps rows with Quantity > 0”.

C:

List expansion creates one row per nested element before its fields are expanded. The present requirement is “Steps in which later steps reference earlier names”; “each array element to become a separate record” is a distinct situation.

D:

M expressions define row-level transformations at data preparation time. That matters for “must branch according to a null-safe status field” rather than the condition “Steps in which later steps reference earlier names”.

Question 150

A source returns nested JSON arrays; the analyst wants each array element to become a separate record. What should be done?

  1. Write a Power Query M conditional expression using if then else.
  2. Preserve the dependency order of Power Query transformation steps.
  3. Expand the list to new rows and then expand its records.
  4. Filter rows in Power Query before loading the table.

Explanation

Correct Answer

C:

Expand the list to new rows and then expand its records. List expansion creates one row per nested element before its fields are expanded.

Incorrect Answers

A:

M expressions define row-level transformations at data preparation time. That matters for “must branch according to a null-safe status field” rather than the condition “each array element to become a separate record”.

B:

M evaluation composes named steps whose downstream references require upstream results. The boundary it addresses is “Steps in which later steps reference earlier names”, while this case concerns “each array element to become a separate record”.

D:

A row filter can reduce the imported dataset and may fold to the source. The deciding difference is “keeps rows with Quantity > 0” versus “each array element to become a separate record”.