Module 4: Verify and Report on Cleaning Results Answers (Part 2: Q16–30)
This is Part 2 of the Module 4 quiz answers for “Verify and Report on Cleaning Results” from the Google Data Analytics Professional Certificate on Coursera.
Here, we’ll walk through questions 16 to 30 with detailed explanations to support your learning.
To find answers to the remaining questions, check out the full module breakdown below:
16. In what step of the data-cleaning process do you find mistakes before you begin analyzing the data?
- Confirming
- Publishing
- Verifying ✅
- Processing
Explanation:
Verification is the final check to identify and correct errors before moving into data analysis.
17. During the data cleaning process you find a significant amount of data that contains irrelevant spaces. Which function do you use to remove leading, trailing, or repeated spaces?
- CUT
- DELETE
- TRIM ✅
- TIDY
Explanation:
TRIM is designed to clean string data by removing unwanted spaces that can interfere with analysis.
18. A data analyst is checking for errors in a dataset. They want to determine how many times the name of a country is in the dataset using a pivot table. What function can they use to find this count?
- COUNTA ✅
- CHECK
- COUNT
- CASE
Explanation:
COUNTA counts how many times non-empty entries (like country names) appear, making it useful with pivot tables for quick summaries.
19. You’re writing the below SQL query and need to change “World Wide Web” to “www”. What function would you use to accomplish this task?
SELECT
_____
WHEN ‘World Wide Web’ THEN ‘www’
END AS some_column
FROM
some_table
- THEN
- CASE ✅
- ELSE
- WHEN
Explanation:
The CASE function allows conditional logic in SQL to replace or transform values based on conditions.
20. What should a data analyst actively track throughout the data cleaning process?
- Additions, changes, and queries
- Errors, deletions, and notes
- Changes, resolutions, and deletions
- Errors, additions, and deletions ✅
Explanation:
Tracking errors, additions, and deletions ensures that data cleaning is thorough and transparent, and it provides a record for future reference.
21. A data analyst is in the verification process and needs to verify the modifications that they have made to the data. What could the analyst reference to find the changes they made throughout data cleaning?
- Changelog ✅
- Notepad
- Spreadsheet
- Metadata
Explanation:
A changelog is a record of all the modifications made during the data cleaning process. It helps analysts verify what changes were made and ensures transparency and accuracy in the workflow.
22. A data analyst commits a query to the repository as a new and improved query. Then, they specify the changes they made and why they made them. This scenario is part of what process?
- Reporting data
- Visualizing data
- Communicating with stakeholders
- Creating a changelog ✅
Explanation:
- A changelog records changes made to data, queries, or processes, helping track improvements and ensuring clarity.
23. The data collected for an analysis project has just been cleaned. What are the next steps for a data analyst? Select all that apply.
- Reporting ✅
- Certification
- Validation
- Verification ✅
Explanation:
- Verification: Ensures the cleaned data meets quality standards and is ready for analysis.
- Reporting: Summarizes findings and communicates insights based on the cleaned data.
Certification is not a standard step for data cleaning or analysis.
Validation might overlap with verification but is not emphasized here.
24. As a data analyst, you will need to keep the big picture in mind throughout any project when verifying data cleaning. What must the analyst do to take a big picture view of the project? Select all that apply.
- Consider the data ✅
- Consider the goal ✅
- Consider the business problem ✅
- Consider the reporting
Explanation:
To see the big picture, analysts need to align their cleaning and verification efforts with the data, the project goals, and the business problem they aim to solve.
25. During the verification process, you find that you missed a few leading spaces during data cleaning. What function can you use to eliminate these spaces?
- TRIM ✅
- TIDY
- CUT
- CROP
Explanation:
The TRIM function removes unwanted spaces (leading, trailing, or both), helping to clean data for consistency and accuracy.
26. Which SQL tool considers one or more conditions, then returns a value as soon as a condition is met?
- THEN
- WHEN
- CASE ✅
- ELSE
Explanation:
The CASE statement allows SQL to evaluate conditions and return results accordingly, making it ideal for conditional logic in queries.
27. Fill in the blank: Documentation is the process of tracking _____ during data cleaning. Select all that apply.
- additions ✅
- deletions ✅
- changes ✅
- inactivity
Explanation:
Documentation captures additions, deletions, and changes, providing a clear record of how data was transformed during cleaning.
28. Fill in the blank: A changelog contains a _____ list of modifications made to a project.
- random
- approximate
- chronological ✅
- synchronized
Explanation:
A changelog maintains a chronological list, helping to understand the sequence of changes and supporting accountability.
29. You start a complex project that will take more than a year to complete. You need to document modifications made to your queries throughout the project. What is the correct way to store these modifications?
- Creating a changelog ✅
- Creating a notepad
- Visualizing data
- Creating a spreadsheet
Explanation:
A changelog ensures all changes are tracked consistently over time, especially crucial for long-term projects.
30. Fill in the blank: A process to confirm that a data-cleaning effort was well-executed and the resulting data is accurate and reliable is known as _____.
- verification ✅
- publishing
- manipulation
- processing
Explanation:
Verification validates that the cleaned data is trustworthy and that cleaning steps were effective and properly implemented.
Hope this helped! Use the buttons below to move to the previous or next part.