Module 4: Verify and report on cleaning results

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In this post, I provide accurate answers and detailed explanations for Module 4: Verify and report on cleaning results of Course 4: Process Data from Dirty to Clean – Google Data Analytics Professional Certificate.

Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.

Test your knowledge on manual data cleaning

Practice Quiz

1. Making sure data is properly verified is an important part of the data-cleaning process. Which of the following tasks are involved in this verification? Select all that apply.

  • Rechecking the data-cleaning effort ✅
  • Considering whether the data is credible and appropriate for the project ✅
  • Asking stakeholders to check and confirm the data is clean
  • Manually fixing any errors found in the data ✅

Explanation:
The verification process ensures the accuracy and reliability of cleaned data:

  • Rechecking the data-cleaning effort ensures no steps were missed.
  • Considering credibility and appropriateness confirms the data aligns with project requirements.
  • Manually fixing errors is essential to address any issues identified during verification.

Asking stakeholders to confirm the data is clean is not part of verification; it’s more about collaboration and validation, not the cleaning process itself.

2. Fill in the blank: To count the total number of spreadsheet values within a specified range, a data analyst uses the _____ function.

  • COUNTA ✅
  • WHOLE
  • TOTAL
  • SUM

Explanation:

  • The COUNTA function counts non-empty cells in a specified range.
  • Other options like WHOLE, TOTAL, and SUM do not serve this purpose.

3. A data analyst is cleaning a dataset with inconsistent formats and repeated cases. They use the TRIM function to remove extra spaces from string variables. What other tools can they use for data cleaning? Select all that apply.

  • Remove duplicates ✅
  • Find and replace ✅
  • Import data
  • Protect sheet

Explanation:

  • Remove duplicates eliminates repeated records.
  • Find and replace standardizes values or corrects errors.
    Other options like Import data and Protect sheet are unrelated to cleaning.

4. To correct a typo in a database column, where should you insert a CASE statement in a query?

  • As a GROUP BY clause
  • As a FROM clause
  • As an ORDER BY clause
  • As a SELECT clause ✅

Explanation:
The CASE statement is used in the SELECT clause to implement conditional logic, correcting typos by mapping incorrect values to correct ones.

Example:SELECT
CASE
WHEN column_name = 'typ0' THEN 'typo'
ELSE column_name
END AS corrected_column
FROM table_name;

Other clauses like GROUP BY, FROM, and ORDER BY are not suitable for such corrections.

Test your knowledge on documenting the cleaning process

Practice Quiz

5. Why is it important for a data analyst to document the evolution of a dataset? Select all that apply.

  • To recover data-cleaning errors ✅
  • To determine the quality of the data ✅
  • To identify best practices in the collection of data
  • To inform other users of changes ✅

Explanation:

  • Recovering data-cleaning errors: Documentation helps identify and reverse any mistakes.
  • Determining data quality: Tracking evolution highlights improvements or issues in the data’s integrity.
  • Informing other users of changes: Ensures all team members are aware of adjustments, fostering collaboration.

To identify best practices in the collection of data is unrelated to documentation of dataset evolution. It pertains more to data collection processes.

6. Fill in the blank: While cleaning data, documentation is used to track _____. Select all that apply.

  • changes ✅
  • errors ✅
  • bias
  • deletions ✅

Explanation:

  • Changes: Tracking modifications ensures clarity and reversibility if issues arise.
  • Errors: Documenting errors enables learning and prevents recurrence.
  • Deletions: Logging removed data ensures transparency and justifies decisions.

Bias is not typically tracked during cleaning but rather during analysis or interpretation phases.

7. Documenting data-cleaning makes it possible to achieve what goals? Select all that apply.

  • Be transparent about your process ✅
  • Keep team members on the same page ✅
  • Demonstrate to project stakeholders that you are accountable ✅
  • Visualize the results of your data analysis

Explanation:

  • Transparency: Shows how data cleaning was conducted, ensuring trust.
  • Team alignment: Documentation ensures all members understand the methods used.
  • Accountability: Demonstrates responsibility and accuracy to stakeholders.

Visualizing the results of your data analysis is not achieved through documentation of data cleaning. This is part of data visualization or analysis phases.

Module 4 challenge

Graded Quiz

8. Verification and reporting come directly before the data-cleaning process.

  • True
  • False

9. What is the first step in the verification process?

  • Compare cleaned data with the original, uncleaned dataset and compare it to what is there now ✅
  • Create a chronological list of modifications made to the data
  • Determine the quality of the data
  • Inform others of your data-cleaning effort

10. Which of the following functions automatically remove extra spaces when cleaning data?

  • SNIP
  • REMOVE
  • TRIM ✅
  • CLEAR

Explanation:

  • The TRIM function removes extra spaces, ensuring data is consistent. Other options like REMOVE, SNIP, and CLEAR are not valid cleaning functions.

11. What tool can a data analyst use to figure out how many identical errors occur in a dataset?

  • CASE
  • COUNTA ✅
  • CONFIRM
  • COUNT

12. Fill in the blank: A data analyst uses the CASE statement to consider one or more _____, then returns a value.

  • additions
  • conditions ✅
  • identifications
  • changes

13. What is the process of tracking changes, additions, deletions, and errors during data cleaning?

  • Recording
  • Observation
  • Cataloging
  • Documentation ✅

Explanation:

  • Documentation involves recording all modifications to ensure transparency and trackability.

14. Fill in the blank: While cleaning data, a data analyst can use a changelog to keep a chronological list of changes they make. They can refer to it during the _____ period if there are errors or questions.

  • presenting
  • verification ✅
  • documentation
  • visualization

15. Reviewing version history is an effective way to view a changelog in SQL.

  • True
  • False ✅

16. In what step of the data-cleaning process do you find mistakes before you begin analyzing the data?

  • Confirming
  • Publishing
  • Verifying ✅
  • Processing

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

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

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 ✅

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

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

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

26. Which SQL tool considers one or more conditions, then returns a value as soon as a condition is met?

  • THEN
  • WHEN
  • CASE ✅
  • ELSE

27. Fill in the blank: Documentation is the process of tracking _____ during data cleaning. Select all that apply.

  • additions ✅
  • deletions ✅
  • changes ✅
  • inactivity

28. Fill in the blank: A changelog contains a _____ list of modifications made to a project.

  • random
  • approximate
  • chronological ✅
  • synchronized

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

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

31. A data analyst is in the verification step. They consider the business problem, the goal, and the data involved in their analytics project. What scenario does this describe?

  • Reporting on the data
  • Considering the stakeholders
  • Seeing the big picture ✅
  • Visualizing the data

32. During data cleaning, you find an error in a username where the ID number was accidentally joined to the user’s last name. You need to figure out if this username has been entered incorrectly more than once in your datasett. If you use a pivot table, what function can you use to determine the number of times this error occurs in your dataset?

  • CASE
  • COUNT
  • COUNTA ✅
  • CHECK

33. You’re working with a dataset that contains categorical variables. You notice that some of the strings are misspelled or are not capitalized. What function can you use to fix these errors when a condition is met?

  • ELSE
  • CASE ✅
  • WHEN
  • THEN

34. A data analyst uses a changelog while cleaning data. What process does a changelog support?

  • Illumination
  • Examination
  • Disclosure
  • Documentation ✅

35. A changelog is essential for storing chronological modifications made during the data cleaning process. When will an analyst refer to the information in the changelog to certify data integrity?

  • Documentation
  • Verification ✅
  • Presenting
  • Visualization

Explanation:

  • During verification, analysts use the changelog to confirm that cleaning processes were executed properly and data integrity is maintained.

36. Fill in the blank: As a data analyst, you should always create a _____ to track your additions, deletions, errors, and changes to a query.

  • notepad
  • database
  • changelog ✅
  • spreadsheet

37. Fill in the blank: TRIM is a function that removes _____ spaces in data. Select all that apply.

  • repeated ✅
  • trailing ✅
  • leading ✅
  • inner

38. While verifying cleaned data, a data analyst encounters a misspelled name. Which function can they use to determine the number of misspelled occurrences in the dataset?

  • CASE
  • CHECK
  • CHECK
  • COUNTA ✅

39 At what point during the analysis process does a data analyst use a changelog?

  • While cleaning the data ✅
  • While visualizing the data
  • While gathering the data
  • While reporting the data

40. Your manager points out an error in a product ID number in your dataset. The Product IDs can be numbers like 42 or text like "CAD-425". Using a pivot table, what function can you use to find how many times this error occurs in the dataset?

  • COUNT
  • CHECK
  • COUNTA ✅
  • CASE

Explanation:

  • The COUNT function tallies occurrences of specific values, making it suitable for identifying errors in datasets.

41. While reviewing your coworker’s data cleaning process, you find a few cases of trailing spaces in the data. What function can you use to remove these spaces?

  • REMOVE TRAILING
  • DELETE
  • CUT
  • TRIM ✅

42. Which of the following queries considers one or more conditions and returns a value as soon as that condition is met?

  • SELECT * WHEN CASE COLUMN = VARIABLE
  • SELECT * CASE IF COLUMN = VARIABLE
  • SELECT * CASE WHEN COLUMN = VARIABLE ✅
  • SELECT * IF CASE COLUMN = VARIABLE

43. Fill in the blank: Once data is clean, a data analyst moves on to _____ and verification.

  • processing
  • confirming
  • publishing
  • reporting ✅

44. A data analyst is starting a large scale project. The project will be crucial to business success and the data analyst needs to keep the big picture at the forefront when verifying their data cleaning. What is the first step in the verification process?

  • Create a chronological list of modifications made to the data
  • Compare cleaned data with the original, uncleaned dataset and compare it to what is there now ✅
  • Inform others of the data-cleaning effort
  • Determine the quality of the data

45. You use SQL to clean your data. You make comments whenever you modify your queries to keep track of any changes. What documentation will this practice help you create when you’re done cleaning the data?

  • A changelog ✅
  • A query repository
  • A new dataset
  • A database

46. A data analyst is starting a large scale project that is crucial to business success. The data analyst needs to remember the big picture when verifying their data cleaning. What is involved when focusing on the big picture-view of the project? Select all that apply.

  • Consider the reporting
  • Consider the business problem ✅
  • Consider the stakeholders
  • Consider the goal ✅

Explanation:

  • Business problem: Ensures the cleaning aligns with solving the primary issue.
  • Goal: Keeps the project’s objective in perspective during verification.

Consider the reporting and Consider the stakeholders are not directly part of focusing on the big picture but rather outcomes of data analysis.

Related contents:

Module 1: The importance of integrity
Module 2: Clean data for more accurate insights
Module 3: Data cleaning with SQL
Module 6: Course wrap-up

You might also like:

Course 1: Foundations: Data, Data, Everywhere
Course 2: Ask Questions to Make Data-Driven Decisions
Course 3: Prepare Data for Exploration
Course 5: Analyze Data to Answer Questions
Course 6: Share Data Through the Art of Visualization
Course 7: Data Analysis with R Programming
Course 8: Google Data Analytics Capstone: Complete a Case Study

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