1.6.Course Challenge - sj50179/Google-Data-Analytics-Professional-Certificate GitHub Wiki

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Question 1

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.

  • Upload the data, then process and analyze it using Tableau.

  • Download the data, then use a spreadsheet to process and analyze it.

  • Use SQL to process and analyze the data.

Correct. Spreadsheets work well for processing and analyzing a small dataset, such as the one you’re using.

Question 2

Scenario 1 continued

Download the dataset directly from the attachment below.

Download

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 an issue you need to fix. Identify the problem.

  • Column E is formatted for currency.

  • The headers in row 1 are bold.

  • The data in column A is sorted alphabetically.

  • There is missing information in row 16.

Correct. Part of the process step is identifying any missing information and ensuring your dataset is complete.

Question 3

Scenario 1 continued

Once you’ve found the missing information, you analyze your dataset. You use a formula to determine how much of each store’s daily sales come from sales of Splashtastic.

During analysis, you create a new column F. At the top of the column, you add: Average Percentage of Total Sales - Splashtastic. What is this column label called?

  • A headline

  • A title

  • A reference

  • An attribute

Correct. An attribute is a characteristic or quality of data used to label a column.

Question 4

Scenario 1 continued

Next, you determine the average total store sales of Splashtastic. To do this, you use a function. Fill in the blank to complete the function correctly: =_____ (E:E).

  • SELECT

  • AVERAGE

  • WHERE

  • FROM

Correct. The function begins with an equal sign (=), then the word AVERAGE. The range is all of column E, represented by E:E.

Question 5

Scenario 1 continued

You’ve reached the share phase of the data analysis process. It involves which of the following? Select all that apply.

  • Prepare a slideshow about Splashtastic’s sales and practice your presentation.

  • Present your findings about Splashtastic to stakeholders.

  • Stop selling Splashtastic because it doesn't represent a large percentage of total sales.

  • Create a data visualization to highlight the Splashtastic sales insights you've discovered.

Correct. The share phase involves creating data visualizations, preparing your presentation, and communicating your findings to stakeholders.

Question 6

Scenario 2, questions 6-10

You’ve been working for the nonprofit National Dental Society (NDS) as a junior data analyst for about two months. The mission of the NDS is to help its members advance the oral health of their patients. NDS members include dentists, hygienists, and dental office support staff.

The NDS is passionate about patient health. Part of this involves automatically scheduling follow-up appointments after crown replacement, emergency dental surgery, and extraction procedures. NDS believes the follow-up is an important step to ensure patient recovery and minimize infection.

Unfortunately, many patients don’t show up for these appointments, so the NDS wants to create a campaign to help its members learn how to encourage their patients to take follow-up appointments seriously. If successful, this will help the NDS achieve its mission of advancing the oral health of all patients.

Your supervisor has just sent you an email saying that you’re doing very well on the team, and he wants to give you some additional responsibility. He describes the issue of many missed follow-up appointments. You are tasked with analyzing data about this problem and presenting your findings using data visualizations.

An NDS member with three dental offices in Colorado offers to share its data on missed appointments. So, your supervisor uses a database query to access the dataset from the dental group. The query instructs the database to retrieve all patient information from the member’s three dental offices, located in zip code 81137.

The table is dental_data_table, and the column name is zip_code. You write the following query, but get an error. What statement will correct the problem?

SELECT *
FROM dental_data_table
WHERE zip code = 81137

  • WHERE zip_code = 81137

  • WHERE 81137

  • WHERE_zip code = 81137

  • zip_code = 81137

Correct. The correct syntax is WHERE zip_code = 81137. WHERE indicates where to look for information. The column name is zip_code. And the database is being asked to return only records matching zip code 81137.

Question 7

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.

You can download the dataset directly below.

Download

Course Challenge Dataset - Scenario 2 - Sheet1.csv 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. Which aspect of patient demographics might get in the way of fairness?

  • The dataset contains patient identification numbers.

  • The dataset indicates which dental procedure the patients had performed.

  • The dataset includes people who all live in the same zip code.

  • The dataset represents people who are single.

Correct. It’s your responsibility as a data analyst to make sure your analysis is fair. Although many zip codes do reflect diverse populations, a better choice would be to include data about people who live in multiple zip codes.

Question 8

Scenario 2 continued

As you’re reviewing the dataset, you notice that there are a disproportionate number of senior citizens. So, you investigate further and find out that this zip code represents a rural community in Colorado with about 800 residents. In addition, there’s a large assisted-living facility in the area. Nearly 300 of the residents in the 81137 zip code live in the facility.

You recognize that’s a sizable number, so you want to find out if age has an effect on a patient’s likelihood to attend a follow-up dental appointment. You analyze the data, and your analysis reveals that older people tend to miss follow-ups more than younger people.

So, you do some research online and discover that people over the age 60 are 50% more likely to miss dentist appointments. Sometimes this is because they’re on a fixed income. Also, many senior citizens lack transportation to get to and from appointments.

With this new knowledge, you write an email to your supervisor expressing your concerns about the dataset. He agrees with your concerns, but he’s also impressed with what you’ve learned and thinks your findings could be very important to the project. He asks you to change the business task. Now, the NDS campaign will be about educating dental offices on the challenges faced by senior citizens and finding ways to help them access quality dental care.

Changing the business task involves which of the following?

  • Defining the new question or problem to be solved

  • Conducting a gap analysis

  • Using a database instead of a spreadsheet

  • Creating a graphical representation of the data

Correct. A business task is the question or problem data analysis answers for a business.

Question 9

Scenario 2 continued

You continue with your analysis. In the end, your findings support what you discovered during your online research: As people get older, they’re less likely to attend follow-up dental visits.

But you’re not done yet. You know that data should be combined with human insights in order to lead to true data-driven decision-making. So, your next step is to share this information with people who are familiar with the problem. They’ll help verify the results of your data analysis.

The people who are familiar with a problem and help verify the results of data analysis include customers and competitors.

  • True

  • False

Correct. Subject-matter experts look at the results of data analysis to identify any inconsistencies, make sense of the gray areas, and eventually validate the choices being made.

Question 10

Scenario 2 continued

The subject-matter experts are impressed by your analysis. The team agrees to move to the next step: data visualization. You know it’s important that stakeholders at NDS can quickly and easily understand that older people are less likely to attend important follow-up dental appointments. This will help them create an effective campaign for members.

It’s time to create your presentation to stakeholders. It will include a data visualization that depicts the relationship between age and follow-up dental appointment attendance rates. For this, a doughnut chart will be most effective.

  • True

  • False

Correct. A doughnut chart is used to depict the relationship between two things. A line chart would be effective for tracking trends over time, such as people attending fewer appointments as they get older.