Welcome to the ultimate guide for Process Data from Dirty to Clean quiz answers! Whether you’re working on practice quizzes to refine your skills or taking graded quizzes to showcase your learning, this guide has everything you need. Covering all modules of the course, this resource will help you master the process of cleaning and transforming data for analysis.
Process Data from Dirty to Clean Quiz Answers – Practice & Graded Quizzes for All Modules
Table of Contents
Process Data from Dirty to Clean Module 01 Quiz Answers
Test your knowledge on data integrity and analytics objectives Quiz Answers
Question 1: Fill in the blank: Data _____ involves the accuracy, completeness, consistency, and trustworthiness of data throughout its lifecycle.
Correct Answer:
- Integrity
Explanation: Data integrity ensures that data remains accurate, consistent, and reliable throughout its lifecycle. This includes maintaining its quality during storage, transfer, and use.
Question 2: Which process do data analysts use to make data more organized and easier to read?
Correct Answer:
- Data manipulation
Explanation: Data manipulation involves transforming and organizing data to make it more readable and suitable for analysis. This could include sorting, filtering, or reformatting the data.
Question 3: Before analysis, a company collects data from countries that use different date formats. Which of the following actions would improve the data integrity?
Correct Answer:
- Change all of the dates to the same format
Explanation: Standardizing the date formats ensures consistency and improves the integrity of the data, making it easier to analyze across datasets from different regions.
Question 4: In this spreadsheet, what common data problem appears in rows 2 and 7?
| First | Last | CustID |
|---|---|---|
| Douglas | Pool | 10794 |
| Ronnie | Mazlan | 10351 |
| Tonya | Butcher | 10990 |
| Yanni | Morningside | 10184 |
| Eliza | Fe | 10212 |
| Travis | Tatien | 10746 |
| Ronnie | Mazlan | 10351 |
Correct Answer:
- Duplicate data
Explanation: Rows 2 and 7 are duplicates of each other, containing the same name and CustID. Duplicate data can lead to inaccuracies and should be resolved to maintain data integrity.
Test your knowledge on insufficient data Quiz Answers
Question 1: What are some strategies data professionals can use when they do not have enough data to meet a business objective? Select all that apply.
Correct Answers:
- Locate another relevant dataset to work with.
- Consider whether it is possible to adjust the objective.
- Use smaller-scale data until they can find more complete data.
Explanation: Data professionals can explore alternative datasets, adjust business objectives to fit the available data, or work with smaller datasets while seeking more comprehensive data. Using hypothetical data, however, is not a reliable strategy as it may introduce bias and lead to inaccurate results.
Question 2: Which of the following are limitations that might lead to insufficient data? Select all that apply.
Correct Answers:
- Data from a single source
- Outdated data
Explanation: Relying on a single source or outdated data can limit the scope and accuracy of analysis. Duplicate data is a different issue that affects data quality, while continually updating data doesn’t inherently lead to insufficiency but might require careful management.
Question 3: A data analyst wants to find out how many middle school students in Helsinki have laptops. It is unlikely that they can survey every middle schooler in the city. Instead, they survey enough students to represent all middle schoolers. This describes what data analytics concept?
Correct Answer:
- Using a sample
Explanation: Sampling is the process of selecting a subset of a population to represent the whole. It is a practical approach when analyzing large populations.
Question 4: Fill in the blank: Sampling _____ occurs when some members of a population are overrepresented or underrepresented in the data.
Correct Answer:
- Bias
Explanation: Sampling bias occurs when a sample does not accurately represent the entire population, leading to skewed or inaccurate results in the analysis.
Test your knowledge on testing your data Quiz Answers
Question 1: Fill in the blank: Hypothesis testing is a way to see if a survey or experiment has _____ results.
Correct Answer:
- Meaningful
Explanation: Hypothesis testing determines whether the results of a survey or experiment are meaningful and not due to random chance. It helps validate the reliability and relevance of findings.
Question 2: A research team conducts an experiment to determine if a new cybersecurity tool is more effective than the previous version. What type of results are required for the experiment to be statistically significant?
Correct Answer:
- Results that are real and not caused by random chance
Explanation: Statistical significance indicates that the results are unlikely to have occurred due to random variation and instead reflect a true effect or difference.
Question 3: In order to have a high confidence level in a customer survey, what should the sample size accurately reflect?
Correct Answer:
- The entire population
Explanation: To achieve a high confidence level, the sample size should represent the entire population. This ensures that the findings are generalizable and reflective of the overall group being studied.
Question 4: Fill in the blank: Typically, a data professional aims to achieve a statistical power of at least _____ to consider their results statistically significant.
Correct Answer:
- 0.8, or 80%
Explanation: Statistical power of 0.8 (or 80%) means there is an 80% chance of detecting an effect if it exists, reducing the likelihood of Type II errors (failing to detect a true effect).
Test your knowledge on margin of error Quiz Answers
Question 1: Fill in the blank: Margin of error is the _____ amount that the sample results are expected to differ from those of the actual population.
Correct Answer:
- Maximum
Explanation: The margin of error represents the maximum expected difference between the sample results and the true population values, accounting for sampling variability.
Question 2: What elements are required to calculate margin of error? Select all that apply.
Correct Answers:
- Sample size
- Confidence level
Explanation: Margin of error is calculated using the sample size and the confidence level. Population size may influence the calculation in rare cases but is typically unnecessary when the sample size is much smaller than the population.
Question 3: In a survey about a new gardening product, 80% of respondents report they would buy the product again. The margin of error for the survey is 5%. Based on that margin of error, what range reflects the population’s true response?
Correct Answer:
- 75-85%
Explanation: The margin of error of 5% means the true population proportion likely falls within 5 percentage points above or below the reported 80%, resulting in the range of 75-85%.
Question 4: In an employee satisfaction survey, 60% of respondents report that they prefer commuting to work via train. The margin of error for the survey is 4%. Based on that margin of error, what range reflects the population’s true response?
Correct Answer:
- 56-64%
Explanation: The margin of error of 4% means the true population proportion likely falls within 4 percentage points above or below the reported 60%, resulting in the range of 56-64%.
Process Data from Dirty to Clean Module 01 Challenge Quiz Answers
Question 1: Fill in the blank: If a test is statistically _____, the results are less likely to be due to random chance and more likely to be due to a real difference between the groups being compared.
Correct Answer:
- Significant
Explanation: Statistical significance indicates that the observed results are unlikely to have occurred due to random chance and are instead attributed to actual differences between the groups.
Question 2: A healthcare provider stores data in patient portals at multiple clinics and its billing system at headquarters. When a doctor makes a change to a patient’s medication in the portal, the change is not reflected in the billing system. This leads to patients being billed for the wrong medications. What data integrity problem does this scenario describe?
Correct Answer:
- Replication
Explanation: Replication issues occur when changes made in one system are not correctly reflected in another, leading to discrepancies and data integrity problems.
Question 3: In a survey about a new type of sustainable material, 55% of respondents report they would be willing to pay more for clothes made from this material. The margin of error for the survey is 3%. Based on that margin of error, what range reflects the population’s true response?
Correct Answer:
- 52-58%
Explanation: The margin of error of 3% means the true population proportion likely falls within 3 percentage points above or below the reported 55%, resulting in the range of 52-58%.
Question 4: A car dealer conducts a survey to understand why customers choose their dealership. They are eager for positive feedback, so they email the survey to only those customers who purchased two or more vehicles from the dealership in the past five years. What is likely to result?
Correct Answer:
- Sampling bias
Explanation: Sampling bias occurs when the survey sample is not representative of the entire population, as in this case where only highly satisfied, repeat customers were surveyed.
Question 5: Fill in the blank: To determine whether a survey or experiment has meaningful _____, a data team uses hypothesis testing.
Correct Answer:
- Significance
Explanation: Hypothesis testing is used to evaluate whether the results of a survey or experiment are statistically significant and meaningful.
Question 6: A data professional in the logistics industry wants to calculate the margin of error for a study about transportation route efficiency. They know the population size and sample size. What must they also know in order to accurately calculate margin of error?
Correct Answer:
- Confidence level
Explanation: To calculate the margin of error, the confidence level is required along with population and sample sizes, as it determines the degree of certainty in the results.
Question 7: A data professional copies a dataset from a USB drive to their computer. They accidentally unplug the USB before the process is complete, which causes the dataset on their computer to be incomplete. What data integrity problem does this scenario describe?
Correct Answer:
- Transfer
Explanation: Transfer issues occur when a file or dataset is not fully or correctly moved between systems or devices, leading to incomplete or corrupted data.
Question 8: Which of the following statements accurately describe sample size, population, and confidence level? Select all that apply.
Correct Answers:
- Random sampling involves selecting a sample from a population so that every possible type of the sample has an equal chance of being chosen.
- Confidence level is the probability that a sample accurately reflects the greater population.
- When data professionals use sample size, they are using a part of a population that is representative of the population.
Explanation: These statements describe key concepts in statistical analysis. Random sampling ensures fairness, confidence level reflects the probability of accuracy, and sample size refers to a representative subset of the population. The 80% confidence level statement is incorrect, as most industries aim for a 90-95% confidence level.
Process Data from Dirty to Clean Module 02 Quiz Answers
Test your knowledge on data cleaning Quiz Answers
Question 1: Which data professionals are most often responsible for ensuring that data is available, secure, and backed up to prevent loss?
Correct Answer:
- Data engineers
Explanation: Data engineers focus on building and maintaining the systems and infrastructure that ensure data is accessible, secure, and backed up to prevent loss.
Question 2: Fill in the blank: If a dataset contains _____, this is an indication that those values do not exist in the dataset.
Correct Answer:
- Nulls
Explanation: Nulls represent missing or nonexistent values in a dataset, indicating that certain data points are not present.
Question 3: A data professional works in a spreadsheet column that can only contain six-digit customer ID numbers. They ensure the data points in the column are always exactly six-digits long using which data analytics tool?
Correct Answer:
- Data formatting
Explanation: Data formatting ensures that the data adheres to specific structural requirements, such as ensuring all customer IDs are six digits long.
Question 4: Fill in the blank: Data validation is a tool for checking the _____ of data before adding or importing it.
Correct Answer:
- Accuracy and quality
Explanation: Data validation is used to verify the accuracy and quality of data to ensure it meets required standards before being added or imported into a system.
Test your knowledge on the first steps toward clean data Quiz Answers
Question 1: To create a clean and consistent visual appearance for a spreadsheet, which tool ensures all font types, sizes, and colors are uniform?
Correct Answer:
- Clear formats
Explanation: The “Clear formats” tool removes all existing formatting, ensuring a clean and consistent visual appearance for font types, sizes, and colors.
Question 2: What is the process of combining two or more datasets into a single dataset?
Correct Answer:
- Data merging
Explanation: Data merging refers to the process of combining multiple datasets into one, aligning fields or rows as necessary.
Question 3: Fill in the blank: In data analytics, _____ describes how well two or more datasets are able to work together.
Correct Answer:
- Compatibility
Explanation: Compatibility in data analytics refers to how well datasets integrate and work together, ensuring seamless analysis.
Question 4: What are some benefits of documenting any errors you find while data cleaning? Select all that apply.
Correct Answers:
- More efficient troubleshooting
- Keep track of changes
- Save time by not repeating errors in the future
Explanation: Documenting errors improves efficiency in identifying and fixing issues, provides a record of changes for transparency, and helps avoid repeating mistakes, saving time in future analyses. Having a backup of your dataset is useful but not directly related to documenting errors.
Test your knowledge on cleaning data in spreadsheets Quiz Answers
Question 1: What is the relationship between a text string and a substring?
Correct Answer:
- A text string is a group of characters within a cell. A substring is a smaller subset of that text string.
Explanation: A text string consists of a sequence of characters (letters, numbers, or symbols) within a cell. A substring refers to a smaller portion or segment of that string extracted based on defined criteria.
Question 2: A data analyst uses the COUNTIF function to count the number of times a value less than 50 occurs between spreadsheet cells D2 through F100. What is the correct syntax?
Correct Answer:
- =COUNTIF(D2:F100,”<50″)
Explanation: The COUNTIF function requires the range (D2:F100) and a condition in quotation marks (“<50”) to count values that meet the criteria.
Question 3: Fill in the blank: To remove leading, trailing, and repeated spaces in data, analysts use the ____ function.
Correct Answer:
- TRIM
Explanation: The TRIM function is used in spreadsheets to clean up text by removing extra spaces, including leading, trailing, and repeated spaces, leaving only single spaces between words.
Question 4: Which spreadsheet tool searches for matches to a specified value in one column, returning a corresponding piece of information from another location?
Correct Answer:
- VLOOKUP
Explanation: The VLOOKUP function searches for a specific value in a column and retrieves a corresponding value from another column within the same row, based on a defined range.
Process Data from Dirty to Clean Module 02 Challenge Quiz Answers
Question 1: To predict future sales trends, a data analyst merges a dataset of historical sales data with a dataset of economic data. What should the data analyst do to ensure the compatibility of the two datasets?
Correct Answer:
- Map the data
Explanation: Data mapping ensures that fields from different datasets are aligned correctly so that they can work together seamlessly. This is crucial when merging datasets with potentially different structures.
Question 2: Fill in the blank: When typing a TRIM function, the correct _____ to follow is =TRIM(range).
Correct Answer:
- syntax
Explanation: The term “syntax” refers to the correct structure and format required to write a function in a spreadsheet.
Question 3: In this spreadsheet, which function will extract Clay Casey’s four-digit postcode?
Correct Answer:
- =RIGHT(C5,4)
Explanation: The RIGHT function extracts a specified number of characters from the rightmost part of a text string. RIGHT(C5,4) pulls the last four characters from cell C5.
Question 4: Fill in the blank: When searching for the value in the first argument of the function, VLOOKUP looks in the _____ column of the specified location.
Correct Answer:
- leftmost
Explanation: VLOOKUP starts its search in the leftmost column of the range specified as its second argument and returns values from the specified column index.
Question 5: In the following spreadsheet, a data professional wants to create product IDs in Column C. The IDs should include the product name from Column A and its version number from Column B. Which function will create the ID Raft05?
Correct Answer:
- =CONCATENATE(A2,B2)
Explanation: The CONCATENATE function combines text from multiple cells into a single string. In this case, it merges the text in A2 and B2.
Question 6: A data analyst wants to know how many cells from A2 through A50 contain numbers below 100. Which of the following COUNTIF statements should they use?
Correct Answer:
- =COUNTIF(A2:A50,”<100″)
Explanation: The COUNTIF function requires the range (A2:A50) and a condition ("<100") in quotation marks to count values less than 100.
Question 7: A data analyst uses a spreadsheet’s Split tool to place each grain and dairy product into new, separate cells. What is the semicolon’s function in this scenario?
Correct Answer:
- Delimiter
Explanation: A delimiter is a character used to separate text strings into individual elements. Here, the semicolon acts as the delimiter.
Question 8: A data professional discovers that a client name has been misspelled numerous times within a spreadsheet. In order to find each of those misspellings, they use a spreadsheet tool that changes how cells appear when values meet specific conditions. What tool do they use?
Correct Answer:
- Conditional formatting
Explanation: Conditional formatting applies visual cues (e.g., colors or styles) to cells when specific conditions are met, helping to identify errors or anomalies.
Question 9: A data analyst is working for a hospital network that has just merged with another hospital system. Both systems have separate databases containing patient information, including demographics, diagnoses, and treatment history. The goal is to combine this patient data into a single, unified database to improve patient care coordination. What is the most important step to take before analyzing the combined patient data?
Correct Answer:
- Data mapping to standardize, merge, and clean the data from both databases.
Explanation: Data mapping is essential for integrating datasets from different sources. It ensures consistency and accuracy by standardizing and cleaning the data.
Question 10: You are a new data analyst and you want to make sure to avoid common pitfalls when cleaning data. Which of the following steps should you take to ensure a smooth and accurate data cleaning process?
Correct Answers:
- Examine the data to understand the data cleaning needs before you start.
- Focus on cleaning a small sample set of the data first.
Explanation: Examining the data upfront identifies the cleaning requirements, and working on a smaller sample allows for more focused and manageable problem-solving. Backups should also be created before cleaning, and errors can be addressed iteratively.
Process Data from Dirty to Clean Module 03 Quiz Answers
Test your knowledge on SQL queries Quiz Answers
Question 1: What are some key benefits of using SQL for data analytics projects? Select all that apply.
Correct Answers:
- Manage huge amounts of data
- Adaptable for multiple database programs
- Powerful data cleaning tools
Explanation: SQL is ideal for managing large datasets, as it can efficiently handle massive amounts of data. It is also adaptable across various database systems, such as MySQL, PostgreSQL, and SQL Server. SQL offers powerful tools for cleaning data, such as string manipulation and filtering. However, SQL doesn’t support inserting images or formatting text like some other tools.
Question 2: Which SQL function cleans string variables by extracting a substring from a string variable?
Correct Answer:
- SUBSTR
Explanation: The SUBSTR function extracts a substring from a string variable in SQL. It allows specifying the starting point and the length of the substring.
Question 3: You are working with a database table that contains data about playlists, and you discover there are duplicate entries. What SQL clause will remove the duplicates from the playlist_id column?
Correct Answer:
- SELECT DISTINCT playlist_id
Explanation: The DISTINCT keyword is used in SQL to return only unique (non-duplicate) values from a specified column. Using SELECT DISTINCT playlist_id will return only the distinct values in the playlist_id column.
Question 4: You are working with a database table that contains data about turtles. What SQL clause will return any turtle ages that are less than three digits long from the turtle_age column?
Correct Answer:
- LENGTH(turtle_age) < 3
Explanation: The LENGTH function in SQL returns the number of characters in a string. To check for turtle ages with fewer than three digits, LENGTH(turtle_age) < 3 will identify values that are shorter than three digits.
Question 5: You are working with a database table that contains data about cookbooks. What SQL clause will retrieve the first eight letters of each data point in the recipe_name column, then store the result in a new column called recipe_listing?
Correct Answer:
- SUBSTR(recipe_name, 1, 8) AS recipe_listing
Explanation: The SUBSTR function extracts a substring from recipe_name, starting at position 1 and including 8 characters. The AS recipe_listing portion renames the result as a new column called recipe_listing.
Process Data from Dirty to Clean Module 03 Challenge Quiz Answers
Question 1: A data professional analyzes medical data for a health insurance company. The dataset they are working with contains millions of rows of data. What tool would be most efficient for the analyst to use?
Correct Answer:
- SQL
Explanation: SQL (Structured Query Language) is the most efficient tool for managing and querying large datasets, especially those containing millions of rows. It allows for fast data retrieval and manipulation, making it ideal for large-scale datasets like the one in this scenario.
Question 2: A data analyst discovers that their database has recognized product price data as text strings. What SQL function can the analyst use to convert the text strings to floats?
Correct Answer:
- CAST
Explanation: The CAST function is used in SQL to convert one data type to another. In this case, the analyst would use CAST to convert the product price data from a text string to a numeric data type like float.
Question 3: A data analyst working on a marketing project uses the SQL command _____ to add a row for a recent product lead to their organization’s database.
Correct Answer:
- INSERT INTO
Explanation: The INSERT INTO command is used in SQL to add a new row of data to an existing table. It is the correct command for inserting a new product lead into the database.
Question 4: You are working with a database table that has columns about products, such as product_name. Which SUBSTR function and AS command will retrieve the first 2 characters of each product name and store the result in a new column called product_ID?
Correct Answer:
- SUBSTR(product_name, 1, 2) AS product_ID
Explanation: The SUBSTR function is used to extract a substring from a string. SUBSTR(product_name, 1, 2) will extract the first two characters of the product_name column, and AS product_ID assigns the result to a new column called product_ID.
Question 5: In SQL, what function can be used to remove leading spaces from a piece of data?
Correct Answer:
- TRIM
Explanation: The TRIM function in SQL removes leading (and trailing) spaces from a string. It is the appropriate function to clean up unnecessary spaces in data.
Question 6: While working with a database table that contains the column invoice_number, you notice that there are some duplicate entries. Which SQL clause would you use in a query to return the invoice_number data without these duplicates?
Correct Answer:
- DISTINCT invoice_number
Explanation: The DISTINCT keyword in SQL is used to eliminate duplicate rows in the result set. In this case, DISTINCT invoice_number will return only unique invoice numbers.
Question 7: A data analyst uses the SQL command _____ to remove unnecessary tables so they do not clutter their organization’s database.
Correct Answer:
- DROP TABLE IF EXISTS
Explanation: The DROP TABLE IF EXISTS command in SQL is used to remove a table from the database if it already exists. This helps keep the database clean and prevents unnecessary tables from taking up space.
Question 8: You are using a database table that includes the column credit_card_numbers, and you want to check for any fraudulent activity. Which SQL clause will help you identify any credit card numbers that are more than 16 characters long?
Correct Answer:
- LENGTH(credit_card_numbers) > 16
Explanation: The LENGTH function is used to determine the length of a string in SQL. In this case, LENGTH(credit_card_numbers) > 16 will identify credit card numbers that are longer than 16 characters, which may be an indicator of fraud.
Question 9: In a table of customer data, you note that some customers have not placed any orders, so the order_value column contains null values. What SQL function can you use to replace these null values with a value in a different column?
Correct Answer:
- COALESCE
Explanation: The COALESCE function in SQL returns the first non-null value in a list of arguments. It is used to replace null values in a column with a specified value, such as using another column to replace null values in the order_value column.
Process Data from Dirty to Clean Module 04 Quiz Answers
Test your knowledge on manual data cleaning Quiz Answers
Question 1: Which of the following tasks are involved in the verification process? Select all that apply.
Correct Answers:
- Considering whether the data is credible and appropriate for the project
- Rechecking the data-cleaning effort
- Asking stakeholders to check and confirm the data is clean
Explanation: The verification process involves confirming that the data is credible, accurate, and relevant for the project. This includes ensuring the data is clean, rechecking the data-cleaning process, and often asking stakeholders to validate the data’s correctness and appropriateness for use.
Question 2: Which function enables a data professional to count the total number of spreadsheet values within a specified range?
Correct Answer:
- COUNTA
Explanation: The COUNTA function in spreadsheets counts the number of non-empty cells within a specified range, making it ideal for counting values in a given range.
Question 3: Fill in the blank: Changelogs are files containing _____ ordered lists of modifications made to a project.
Correct Answer:
- chronologically
Explanation: Changelogs typically contain chronologically ordered lists, meaning the most recent modifications are listed first. This helps track changes over time in an organized manner.
Question 4: A data professional discovers that SUV is spelled SWV in the database column car_types. Which CASE clause will enable them to correct the misspellings?
Correct Answer:
- CASE WHEN car_types = ‘SWV’ THEN ‘SUV’
Explanation: The correct CASE syntax for correcting a misspelling in a database is CASE WHEN car_types = 'SWV' THEN 'SUV'. This statement checks if the value in the car_types column is ‘SWV’ and replaces it with ‘SUV’.
Test your knowledge on documenting the cleaning process Quiz Answers
Question 1: What objectives can be achieved by documenting the evolution of a dataset? Select all that apply.
Correct Answers:
- Communicate data insights to stakeholders
- Determine the quality of the data
- Inform other users of changes
Explanation: Documenting the evolution of a dataset helps in communicating insights to stakeholders, determining data quality, and informing other users about changes made to the dataset. This documentation can serve as a reference for future analysis and decision-making.
Question 2: Fill in the blank: After a change to a query is submitted, all team members will be able to access the new query once they _____ the most up-to-date version control system.
Correct Answer:
- sync to
Explanation: The correct term is “sync to,” meaning that team members need to synchronize their local version of the query with the most up-to-date version control system to access the latest changes.
Question 3: What information is typically included in a changelog? Select all that apply.
Correct Answers:
- The component that changed and the reason why
- The date of the change
- A description of the change
Explanation: A changelog typically includes details like the component that changed, the reason for the change, the date it was made, and a description of the change itself. FAQs are not typically part of a changelog.
Question 4: A data professional makes a change to a file. Then, they ask a colleague to evaluate the change to identify any potential issues. What does this scenario describe?
Correct Answer:
- Code review
Explanation: This scenario describes a “code review,” where a colleague reviews a change made to a file to identify any potential issues before the change is finalized or implemented.
Process Data from Dirty to Clean Module 04 Challenge Quiz Answers
Question 1: Fill in the blank: A software engineer accesses the source of code for a new app in a _____, which allows them to revert to previous versions of the code if a problem is discovered.
Correct Answer:
- version control system
Explanation: A version control system is used by software engineers to manage changes to code. It allows them to track versions and revert to previous ones if needed.
Question 2: A junior data analyst analyzes data about a healthcare clinical trial. During the verification process, they prioritize the big picture view of ensuring the medication is safe and effective. What steps do they take to achieve this goal? Select all that apply.
Correct Answers:
- Consider the data
- Consider the reporting
- Consider the goal
- Consider the business problem
Explanation: During the verification process, the data analyst should consider the data, reporting, the ultimate goal, and the business problem to ensure the medication is safe and effective. All of these factors help provide a comprehensive understanding and correct analysis.
Question 3: Which SQL clause will consider the condition ‘Barbados’ and return the value ‘island’ when that condition is met?
Correct Answer:
- CASE WHEN country = ‘Barbados’ THEN ‘island’ END
Explanation: The correct SQL clause to check the condition and return a specific value is CASE WHEN condition THEN result END. In this case, the condition is country = 'Barbados' and the result is 'island'.
Question 4: What is the process of tracking changes, additions, deletions, and errors during data cleaning?
Correct Answer:
- Documentation
Explanation: The process of tracking changes, additions, deletions, and errors during data cleaning is referred to as documentation. It helps to keep a clear record of modifications made during the cleaning process.
Question 5: During verification, you wonder if one of your data modifications was an effective update. What can you reference to revisit the modification and your reasoning behind it?
Correct Answer:
- Changelog
Explanation: A changelog records all changes made to data, including the reasons for the modifications. It serves as a reference to revisit previous changes and understand the reasoning behind them.
Question 6: A data analyst uses a pivot table in Google Sheets to determine how many times a particular country name occurs within a dataset. What function will provide the required information?
Correct Answer:
- COUNTA
Explanation: The COUNTA function in Google Sheets counts the number of non-empty cells, which can be used to determine how many times a particular country name occurs within a dataset.
Question 7: Which of the following statements accurately describe code review and code commit? Select all that apply.
Correct Answers:
- An example of code review is a data professional asking a colleague to assess their SQL query.
- Code review occurs prior to code commit.
- Code commit might involve updating code within a version control system.
Explanation: Code review is the process of evaluating code for issues or improvements before it is committed to the version control system. Code commit involves adding the code to the system, often after the review.
Question 8: Fill in the blank: To update a client’s last name in their spreadsheet, a data professional uses _____ to search for any instance of “Reynolds” and change it to “Mehta.”
Correct Answer:
- find and replace
Explanation: The find and replace tool is used in spreadsheets to search for specific values (like “Reynolds”) and replace them with new values (like “Mehta”).
Frequently Asked Questions (FAQ)
Are the Process Data from Dirty to Clean quiz answers accurate?
Yes, these answers are verified and align perfectly with the latest course content.
Can I use these answers for both practice and graded quizzes?
Definitely! These answers are designed to assist you with both practice and graded quizzes, making your preparation more effective.
Does this guide include solutions for all modules in the course?
Absolutely! This guide covers every module to ensure you’re well-prepared for each quiz.
Conclusion
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All Course Quiz Answers of Google Data Analytics Professional Certificate
Course 01: Foundations: Data, Data, Everywhere
Course 02: Ask Questions to Make Data-Driven Decisions
Course 03: Prepare Data for Exploration
Course 04: Process Data from Dirty to Clean
Course 05: Analyze Data to Answer Questions
Course 06: Share Data Through the Art of Visualization
Course 07: Data Analysis with R Programming
Course 08: Google Data Analytics Capstone: Complete a Case Study