Foundations: Data, Data Everywhere Course Challenge Answers (Part 2: Q11–20)
This is Part 2 of the Module 5 quiz answers for “Foundations: Data, Data Everywhere Course Challenge” from the Google Data Analytics Professional Certificate on Coursera.
Here, we’ll walk through questions 11 to 20 with detailed explanations to support your learning.
To find answers to the remaining questions, check out the full module breakdown below:
11. Scenario 1, question 1-5
You’ve just started a new job as a data analyst. You’re working for a midsized pharmacy chain with 38 stores in the American Southwest. Your supervisor shares a new data analysis project with you.
She explains that the pharmacy is considering discontinuing a bubble bath product called Splashtastic. Your supervisor wants you to analyze sales data and determine what percentage of each store’s total daily sales come from that product. Then, you’ll present your findings to leadership.
You know that it's important to follow each step of the data analysis process: ask, prepare, process, analyze, share, and act. So, you begin by defining the problem and making sure you fully understand stakeholder expectations.
One of the questions you ask is where to find the dataset you’ll be working with. Your supervisor explains that the company database has all the information you need.
Next, you continue to the prepare step. You access the database and write a query to retrieve data about Splashtastic. You notice that there are only 38 rows of data, representing the company’s 38 stores. In addition, your dataset contains five columns: Store Number, Average Daily Customers, Average Daily Splashtastic Sales (Units), Average Daily Splashtastic Sales (Dollars), and Average Total Daily Sales (All Products).
Considering the size of your dataset, you decide to download the data, then import it into a spreadsheet. What step of the data analysis process are you in?
- Analyze
- Destroy
- Process ✅
- Copy
Explanation:
At this point, you’ve retrieved the dataset and moved it into a spreadsheet. You’re preparing to clean and validate the data. The process phase involves checking data for errors or inconsistencies before analysis. Since you’re preparing the data for analysis, you’re in the process step.
12. Scenario 1 continued
You’ve downloaded the data from your company database and imported it into a spreadsheet. To use the dataset for this scenario, click the link below and select “Use Template.”
Link to template: Course Challenge - Scenario 1
OR
If you don’t have a Google account, you can download the template directly from the attachment below.
Now, it’s time to process the data. As you know, this step involves finding and eliminating errors and inaccuracies that can get in the way of your results. While cleaning the data, you notice that information about Splashtastic is missing in row 16. Which of the following would be an appropriate course of action?
- Sort the spreadsheet so the row with missing data is at the bottom.
- Delete the row with the missing data point.
- Investigate previous projects and see how this was dealt with there. ✅
- Replace the row with the average values of the other data points.
Explanation:
When dealing with missing data, it’s best practice to understand how similar issues were handled in the past. Simply deleting or replacing data without context may skew results. Looking at precedent helps ensure consistency and accuracy.
13. Scenario 1 continued
Once you’ve found the missing information, you analyze your dataset.
During analysis, you create a new column F. At the top of the column, you add: Average Percentage of Total Sales - Splashtastic. In data analytics, this column label is called an attribute.
- True ✅
- False
Explanation:
Yes, in data analytics, a column name or label is referred to as an attribute. It describes the characteristic of the data in that column—in this case, the percentage of Splashtastic sales.
14. Scenario 1 continued
Fill in the blank: You’ve reached the share phase of the data analysis process. One of the things that you can do in this phase is to prepare a _____ about Splashtastic’s sales and practice your presentation.
- slideshow ✅
- record
- finding
- prediction
Explanation:
In the share phase, you present findings to stakeholders. A slideshow is a common way to summarize and communicate insights clearly and visually to a non-technical audience.
15. Scenario 2 continued
The dataset your supervisor retrieved and imported into a spreadsheet includes a list of patients, their demographic information, dental procedure types, and whether they attended their follow-up appointment. To use the dataset for this scenario, click the link below and select “Use Template.”
Link to template: Course Challenge - Scenario 2
OR
If you don’t have a Google account, you can download the template directly from the attachment below.
The patient demographic information includes data such as age and gender. As you’re learning, it’s your responsibility as a data analyst to make sure your analysis is fair. Looking at the geographic data, you notice that all the patients live in the same zip code. How might this negatively impact the analysis?
- It could cause the analysis to be useless.
- It could cause the analysis to be unbiased.
- It could cause the analysis to be fair.
- It could cause the analysis to be biased. ✅
Explanation:
When your dataset lacks geographic diversity, it may not represent the entire customer population. This can introduce bias, making results unreliable or not generalizable.
16. Scenario 1, question 1-5
You’ve just started a new job as a data analyst. You’re working for a midsized pharmacy chain with 38 stores in the American Southwest. Your supervisor shares a new data analysis project with you.
She explains that the pharmacy is considering discontinuing a bubble bath product called Splashtastic. Your supervisor wants you to analyze sales data and determine what percentage of each store’s total daily sales come from that product. Then, you’ll present your findings to leadership.
You know that it's important to follow each step of the data analysis process: ask, prepare, process, analyze, share, and act. So, you begin by defining the problem and making sure you fully understand stakeholder expectations.
One of the questions you ask is where to find the dataset you’ll be working with. Your supervisor explains that the company database has all the information you need.
Next, you continue to the prepare step. You access the database and write a query to retrieve data about Splashtastic. You notice that there are only 38 rows of data, representing the company’s 38 stores. In addition, your dataset contains five columns: Store Number, Average Daily Customers, Average Daily Splashtastic Sales (Units), Average Daily Splashtastic Sales (Dollars), and Average Total Daily Sales (All Products).
Considering the size of your dataset, what’s the best way to proceed with the process and analyze steps?
- Continue using the company database to process and analyze the data.
- Use SQL to process and analyze the data.
- Download the data, then use a spreadsheet to process and analyze it. ✅
- Upload the data, then process and analyze it using Tableau.
Explanation:
With just 38 rows, it’s more efficient to use a spreadsheet rather than complex tools like SQL or Tableau. Spreadsheets are ideal for smaller, manageable datasets.
17. Scenario 1 continued
You’ve downloaded the data from your company database and imported it into a spreadsheet. To use the dataset for this scenario, click the link below and select “Use Template.”
Link to template: Course Challenge - Scenario 1
OR
If you don’t have a Google account, you can download the template directly from the attachment below.
Now, it’s time to process the data. As you know, this step involves finding and eliminating errors and inaccuracies that can get in the way of your results. While cleaning the data, you notice there’s missing data in one of the rows. What might you do to fix this problem? Select all that apply.
- Ask a colleague on your team how they’ve handled similar issues in the past ✅
- Sort the spreadsheet so the row with missing data is at the bottom
- Delete the row with the missing data point
- Ask you supervisor for guidance ✅
Explanation:
Getting advice from experienced colleagues or guidance from a supervisor ensures you handle the issue appropriately and consistently with organizational standards. Sorting or deleting without context might not be the best approach.
18. Scenario 1 continued
Once you’ve found the missing information, you analyze your dataset. During analysis, you create a new column F. You label the top of the column Average Percentage of Total Sales - Splashtastic.
Fill in the blank: The column label you add to column F is known as ______.
- an attribute ✅
- a reference
- an observation
- a title
Explanation:
Column labels in datasets are often referred to as attributes because they describe the data contained in the column.
19. Scenario 1 continued
Next, you determine the average total daily sales over the past 12 months at all stores. The range that contains these sales is E2:E39. To do this, you use a function. Fill in the blank to complete the function correctly: =AVERAGE_____.
- (E2:E39) ✅
- E2:E39
- (E2-E39)
- E2-E39
Explanation:
The correct syntax for calculating the average in Excel or Google Sheets is =AVERAGE(range). In this case, the range is E2 to E39, which includes the average total daily sales.
20. Scenario 1 continued
You’ve reached the share phase of the data analysis process. What can you do in this phase to highlight the Splashtastic sales insights you've discovered?
- Compile a record of the data.
- Create a data visualization. ✅
- Establish a repository for the data.
- Revisit the analyze phase.
Explanation:
One of the most effective ways to share insights is by creating data visualizations (like charts or graphs). These help stakeholders quickly understand the data story and support decision-making.
Hope this helped! Use the buttons below to move to the previous or next part.