A data analyst is working with a dataset that has a 'Phone Number' column. Some entries contain dashes, some contain parentheses, and some are missing the area code. The analyst needs to standardize the phone numbers to a consistent format. What should the analyst do in Power Query?

Use the Extract feature to pull out the digits only.

Use the Replace Values feature to remove dashes and parentheses.

Use a combination of Replace Values, Extract, and Conditional Column to clean and standardize the column.

Use the Conditional Column feature to add a default area code for missing ones.

A data analyst is reviewing a dataset of employee records. The 'Salary' column shows a minimum of $30,000 and a maximum of $500,000. The analyst suspects that some values are outliers. What should the analyst do to investigate the distribution of salary values?

Use the Column Distribution pane to view the frequency of each salary value.

Use the Column Statistics pane to view the average and median salary.

Use the Sort feature to order the salary column.

Use the Replace Values feature to remove the outliers.

A data analyst imports a table with a 'Region' column that has nulls for about 5% of rows. The analyst needs to fill these nulls with a value that will not distort regional reporting. The analyst has a separate lookup table that maps postal codes to regions. What should the analyst do?

Use the Replace Values feature to replace nulls with the most common region.

Use the Merge Queries feature to join the lookup table and fill the nulls based on postal code.

Replace nulls with 'Unknown' in the 'Region' column.

A data analyst imports a transaction table where the 'Amount' column contains some values that are negative, which are valid refunds, and some values that are extremely large (e.g., 999999) that are known placeholders for missing data. The analyst needs to calculate net revenue. What should the analyst do to handle the placeholders without affecting valid refunds?

Replace all values greater than 100000 with 0.

Filter out all negative values.

Change the data type to Decimal and leave the values.

A data analyst imports a product table and notices that the 'Price' column contains a value of -1 for products that are discontinued. The analyst needs to report only active products with valid prices. What should the analyst do in Power Query?

Sort the Price column descending.

Filter out rows where Price is less than 0.

Change the data type of Price to Whole Number.

Microsoft Certified:Power BI Data Analyst Associate

Domain 1Objective 2

Profile and Clean the Data PL-300 Practice Questions (Page 6)

Part of the Prepare the data domain, which accounts for 25–30% of the PL-300 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~10–20 in this domain), expect 3–7 from this objective — we provide 35 practice questions to prepare you well beyond it. (estimate)

35questions here

7free pages

7concepts

25–30%of the exam

Questions 26–30

26application · medium
A data analyst is working with a dataset that has a 'Phone Number' column. Some entries contain dashes, some contain parentheses, and some are missing the area code. The analyst needs to standardize the phone numbers to a consistent format. What should the analyst do in Power Query?
Select an answer first
27application · medium
A data analyst is reviewing a dataset of employee records. The 'Salary' column shows a minimum of $30,000 and a maximum of $500,000. The analyst suspects that some values are outliers. What should the analyst do to investigate the distribution of salary values?
Select an answer first
28application · medium
A data analyst imports a table with a 'Region' column that has nulls for about 5% of rows. The analyst needs to fill these nulls with a value that will not distort regional reporting. The analyst has a separate lookup table that maps postal codes to regions. What should the analyst do?
Select an answer first
29expert · hard
A data analyst imports a transaction table where the 'Amount' column contains some values that are negative, which are valid refunds, and some values that are extremely large (e.g., 999999) that are known placeholders for missing data. The analyst needs to calculate net revenue. What should the analyst do to handle the placeholders without affecting valid refunds?
Select an answer first
30application · medium
A data analyst imports a product table and notices that the 'Price' column contains a value of -1 for products that are discontinued. The analyst needs to report only active products with valid prices. What should the analyst do in Power Query?
Select an answer first

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