Course 3: Prepare Data for Exploration, all weekly challenge quiz answers of this course are provided in this article from week 1 to week 4 including optional quiz answers for week 5 to help students solving this exam.

Prepare Data for Exploration Weekly Challenge 1 Answers

Q1. If you have a short time frame for data collection and need an answer immediately, you would have to use historical data.

• True
• False

Q2. Which of the following is an example of continuous data?

• Box office returns
• Movie run time
• Movie budget
• Leading actors in movie

Q3. Which of the following questions collects nominal qualitative data?

• Is this your first time dining at this restaurant?
• How many people do you usually dine with?
• On a scale of 1-10, how would you rate your service today?
• How many times have you dined at this restaurant?

Q4. Which of the following is a benefit of internal data?

• Internal data is less vulnerable to biased collection.
• Internal data is more relevant to the problem.
• Internal data is more reliable and easier to collect.
• Internal data is less likely to need cleaning.

Q5. A social media post is an example of structured data.

• True
• False

Q6. Fill in the blank: A Boolean data type can have _____ possible values.

• two
• three
• infinite
• 10

Q7. In long data, separate columns contain the values and the context for the values, respectively. What does each column contain in wide data?

• A specific constraint
• A unique format
• A specific data type
• A unique data variable

Q8. A data analyst is working in a spreadsheet application. They use Save As to change the file type from .XLS to .CSV. This is an example of a data transformation.

• True
• False

Prepare Data for Exploration Weekly Challenge 2 Answers

Q1. Fill in the blank: A preference in favor of or against a person, group of people, or thing is called _____. It is an error in data analytics that can systematically skew results in a certain direction.

• data interoperability
• data collection
• data anonymization
• data bias

Q2. A university surveys its student-athletes about their experience in college sports. The survey only includes student-athletes with scholarships. What type of bias is this an example of?

• Interpretation bias
• Confirmation bias
• Sampling bias
• Observer bias

Q3. Which of the following are qualities of unreliable data? Select all that apply.

• Biased
• Vetted
• Inaccurate
• Incomplete

Q4. In data ethics, consent gives an individual the right to know the answers to which of the following questions? Select all that apply.

• How will my data be used?
• Why am I being forced to share my data?
• Why is my data being collected?
• How long will my data be stored?

Q5. An individual who provides their data has the right to know and understand all of the data-processing activities and algorithms used on that data. This concept refers to which aspect of data ethics?

• Transaction transparency
• Ownership
• Consent
• Currency

Q6. What is data privacy?

• Providing free access, usage, and sharing of data
• Applying well-founded standards of right and wrong that dictate how data is collected, shared, and used
• Searching for or interpreting supporting information
• Preserving a data subject’s information and activity for all data transactions

Q7. Data anonymization applies to both text and images.

• True
• False

Q8. The government of a large city collects data on the quality of the city’s infrastructure. Any business, nonprofit organization, or citizen can access the government’s databases and re-use or redistribute the data. Is this an example of open data?

• Yes
• No

Prepare Data for Exploration Weekly Challenge 3 Answers

Q1. Primary and foreign keys are two connected identifiers within separate tables. These tables exist in what kind of database?

• Primary
• Relational
• Normalized
• Metadata

Q2. Metadata is data about data. What kinds of information can metadata offer about a particular dataset? Select all that apply.

• How to combine the data with another dataset
• Which analyses to perform on the data
• If the data is clean and reliable
• What kinds of data it contains

Q3. Think about data as a student at a high school. In this metaphor, which of the following are examples of metadata? Select all that apply.

• Classes the student is enrolled in
• Student’s ID number
• Grades the student earns
• Student’s enrollment date

Q4. Think about data as a refrigerator. Which kind of metadata is the refrigerator’s product number?

• Redundant
• Administrative
• Structural
• Descriptive

Q5. What is the process that data analysts use to ensure the formal management of their company’s data assets?

• Data integrity
• Data governance
• Data mapping
• Data aggregation

Q6. Describe the key differences between a star and a snowflake schema. Select all that apply.

• A star schema enables very fast data processing.
• A snowflake schema enables very fast data processing. This should not be selected
• A snowflake schema has one or more fact tables referencing any number of dimension tables. A star schema is an extension of a snowflake schema, with more dimensions and subdimensions.
• A star schema has one or more fact tables referencing any number of dimension tables. A snowflake schema is an extension of a star schema, with more dimensions and subdimensions.

Q7. What are some key benefits of using external data? Select all that apply.

• External data is always reliable.
• External data is free to use.
• External data has broad reach.
• External data provides industry-level perspectives.

Q8. A data analyst reviews a database of Wisconsin car sales to find the last five car models sold in Milwaukee in 2019. How can they sort and filter the data to return the last five cars at the top? Select all that apply.

• Filter out sales outside of Milwaukee
• Filter out sales not in 2019
• Sort by date in ascending order
• Sort by date in descending order

Prepare Data for Exploration Weekly Challenge 4 Answers

Q1. Fill in the blank: Naming conventions are _____ that describe a file’s content, creation date, or version.

• frequent suggestions
• common verifications
• general attributes
• consistent guidelines

Q2. A data analytics team uses data about data to indicate consistent naming conventions for a project. What type of data is involved in this scenario?

• Metadata
• Long data
• Aggregated data
• Big data

Q3. A data analyst creates a file that lists people who donated to their organization’s fund drive. An effective name for the file is: FundDriveDonors_Feb2022_V3.

• True
• False

Q4. Foldering may be used by data analysts to organize folders into what?

• Databases
• Subfolders
• Versions
• Tables

Q5. Data analysts use archiving to separate current from past work. What does this process involve?

• Reviewing current data files to confirm they’ve been cleaned
• Moving files from completed projects to another location
• Reorganizing and renaming current files
• Using secure data-erase software to destroy old files

Q6. Fill in the blank: Data analysts create _____ to structure their folders.

• hierarchies
• ladders
• sequences
• scales

Q7. A data analyst wants to ensure only people on their analytics team can access, edit, and download a spreadsheet. They can use which of the following tools? Select all that apply.

• Sharing permissions
• Encryption
• Templates
• Filtering

Q8. To reduce clutter, a data analyst hides cells that contain long, complex formulas. To view the formulas again, the analyst will need to adjust the spreadsheet sharing or encryption settings.

• True
• False

Prepare Data for Exploration Week 05 Quiz Answers!

> Optional: Engaging in the data community.

Scenario 1, questions 1-5

Q1. You’ve been working at a data analytics consulting company for the past six months. Your team helps restaurants use their data to better understand customer preferences and identify opportunities to become more profitable.

To do this, your team analyzes customer feedback to improve restaurant performance. You use data to help restaurants make better staffing decisions and drive customer loyalty. Your analysis can even track the number of times a customer requests a new dish or ingredient in order to revise restaurant menus.

Currently, you’re working with a vegetarian sandwich restaurant called Garden. The owner wants to make food deliveries more efficient and profitable. To accomplish this goal, your team will use delivery data to better understand when orders leave Garden, when they get to the customer, and overall customer satisfaction with the orders.

Before project kickoff, you attend a discovery session with the vice president of customer experience at Garden. He shares information to help your team better understand the business and project objectives. As a follow-up, he sends you an email with datasets.

Click below to read the email: C3 Scenario 1_Client Email.pdf

And click below to access the datasets:

Course 3 Final Challenge Data Sets – Customer survey data (1).csv

Course 3 Final Challenge Data Sets – Delivery times_distance (1).csv

Reviewing the data enables you to describe how you will use it to achieve your client’s goals. First, you notice that all of the data is first-party data. What does this mean?

• It’s subjective data that measures qualities and characteristics.
• It’s data that was collected by Garden employees using their own resources.
• It’s a type of data that’s categorized without a set order.
• It’s data that was collected from outside sources.

Q2. Next, you review the customer satisfaction survey data:

CustomerSurveyData – Customer survey data.csv

The question in column E asks, “Was your order accurate? Please respond yes or no.” What kind of data is this?

• Clean data
• Ordinal data
• Second-party data
• Boolean data

Q3. Now, you review the data on delivery times and the distance of customers from the restaurant:

DeliveryTimes_DistanceData – Delivery times_distance.csv

The data in column E shows the duration of each delivery. What type of data is this? Select all that apply.

• Quantitative data
• Qualitative data
• Discrete data
• Continuous data

Q4. The next thing you review is the file containing pictures of sandwich deliveries over a period of 30 days. This is an example of structured data.

• True
• False

Q5. Now that you’re familiar with the data, you want to build trust with the team at Garden.

What actions should you take when working with their data? Select all that apply.

• Keep the data safe by implementing data-security measures, such as password protection and user permissions.
• Organize the data using effective naming conventions.
• Share the client’s data with other delivery restaurants to compare performance.
• Post on social media that you’re working with Garden and would like feedback from any of your contacts who have ordered there before.

Scenario 2, questions 6-10

Q6. You’ve completed this program and are interviewing for a junior data scientist position at a company called Sewati Financial Services.

Click below to review the job description:

C3 Course Challenge Junior Data Scientist Job Description .pdf

So far, you’ve successfully completed the first interview with a recruiter. They arrange your second interview with the team at Sewati Financial Services.

Click below to read the email from the human resources director:

Course 3 Scenario 2_Second Interview Email.pdf

You arrive 15 minutes early for your interview. Soon, you are escorted into a conference room, where you meet Kai Harvey, the senior manager of strategy. After welcoming you, he begins the behavioral interview.

Q6. Consider and respond to the following question. Select all that apply.

Our data analytics team often surveys clients to get their feedback. If you were on the team, how would you ensure the results do not favor a particular person, group of people, or thing?

• Instruct participants to share their name and contact information.
• Ensure the survey sample represents the population as a whole.
• Make sure the wording of the survey question does not encourage a specific response from participants.
• Give participants enough time to answer each survey question.

Q7. Consider and respond to the following question. Select all that apply.

Our data analytics team often uses both internal and external data. Describe the difference between the two.

• Internal data lives within a company’s own systems. External data lives outside the organization.
• External data is typically generated from within the company. Internal data is generated outside the organization.
• Internal data is typically generated from within the company. External data is generated outside the organization.
• External data lives within a company’s own systems. Internal data lives outside the organization.

Q8. Consider and respond to the following question. Select all that apply.

Our analysts often work with the same spreadsheet, but for different purposes. How would you use filtering to help in this situation?

• Use filters to highlight the header row
• Use filters to simplify a spreadsheet by only showing you only the information you need.
• Use filters to sort the data in a meaningful order
• Use filters to show only the data that meets a specific criteria while hiding the rest

Q9. Next, your interviewer wants to better understand your knowledge of basic SQL commands. He asks: How would you write a query that retrieves only data about people with the last name Hassan from the Clients table in our database?

• SELECT DATA FROM Clients WHERE ‘Hassan’
• SELECT Clients WHERE Last_Name= ‘Hassan’ FROM *
• SELECT * FROM Clients WHERE Last_Name= ‘Hassan’
• SELECT All WHERE Last_Name ‘Hassan’ FROM Clients

Q10. For your final question, your interviewer explains that Sewati Financial Services cares about its clients’ trust, and this is an important responsibility for the data analytics team. They do this by:

• protecting clients from unauthorized access to their private data
• ensuring freedom from inappropriate use of client data
• giving consent to use someone’s data

He asks: Which data analytics practice does this describe?

• Encryption
• Data privacy
• Sharing permissions
• Bias