Consider where the data came from ✓ Show
Correct Create reports for stakeholders Ask questions about the data ✓ Correct Use descriptive column headers ✓ Correct Recommended textbook solutionsIntroduction to Algorithms3rd EditionCharles E. Leiserson, Clifford Stein, Ronald L. Rivest, Thomas H. Cormen 726 solutions Operating System Concepts9th EditionAbraham Silberschatz, Greg Gagne, Peter B. Galvin 489 solutions
Service Management: Operations, Strategy, and Information Technology7th EditionJames Fitzsimmons, Mona Fitzsimmons 103 solutions
Service Management: Operations, Strategy, and Information Technology7th EditionJames Fitzsimmons, Mona Fitzsimmons 103 solutions Coursera Google Data Analytics Professional Certificate Course 3 – Prepare Data for Exploration quiz answers to all weekly
questions (weeks 1 – 5): You may also be interested in Google Data Analytics Professional Certificate Course 1: Foundations – Cliffs Notes. We all generate lots of data in our daily lives. In this part of the course, you’ll check out
how we generate data and how analysts decide which data to collect for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for exploration. Fill in the blank: The running time of a movie is an example of _ data. Running times of movies are an example of continuous data, which is measured and can have almost any numeric value. What are the characteristics of unstructured data? Select all that apply. Unstructured data is not organized, although it may have an internal structure. Structured data enables data to be grouped together to form relations. This makes it easier for analysts to do what with the data? Select all that apply. Structured data that is grouped together to form relations enables analysts
to more easily store, search, and analyze the data. Which of the following is an example of unstructured data? An example of unstructured data is an email message. Other examples of unstructured data are video files and social media content. Which method of data-collection is most often used by scientists? Observation is the method of data-collection most often used by scientists. Fill in the blank: Organizations such as the U.S. Centers for Disease Control (CDC) often use data collected from other organizations. Data gathered by hospitals, then collected by the CDC
is an example of _. Data gathered by hospitals, then collected by the CDC is an example of second-party data. Question 3A data analyst is working for a company that’s about to launch a new product. The analyst needs to collect qualitative data from customers during the product launch. What is the quickest, most accurate, and most relevant method of data collection in this scenario?
L4 Explore data types, fields, and valuesQuestion 1You’re working as a data analyst and you use a formula to average data in a spreadsheet. You receive an error based on the data type. Which data types in cells may have caused the error? Select all that apply.
Question 2The Boolean operator Not performs which of the following actions?
Question 3Fill in the blank: Internet search engines are an everyday example of how Boolean operators are used. The Boolean operator _ expands the number of results when used in a keyword search.
Question 4Which of the following statements accurately describes a key difference between wide and long data?
Question 5Data transformation enables you to do what with your data?
Weekly challenge 1Question 1If you have a short time frame for data collection and need an answer immediately, you would have to use historical data.
Question 2Which of the following is an example of continuous data?
Question 3Which of the following questions collects nominal qualitative data?
Question 4Which of the following is a benefit of internal data?
Question 5A social media post is an example of structured data.
Question 6Fill in the blank: A Boolean data type can have _ possible values.
Question 7In long data, separate columns contain the values and the context for the values, respectively. What does each column contain in wide data?
Question 8A 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.
Week 2: Bias, credibility, privacy, ethics, and accessWhen data analysts work with data, they always check that the data is unbiased and credible. In this part of the course, you’ll learn how to identify different types of bias in data and how to ensure credibility in your data. You’ll also explore open data and the relationship between and importance of data ethics and data privacy. Learning Objectives
Answers to week 2 quiz questionsL2 Unbiased and objective dataQuestion 1Which of the following are examples of sampling bias? Select all that apply.
Question 2Two doctors look at the exact same image of a brain scan. The image is inconclusive, yet one doctor sees evidence of an abnormality in the brain. The other doctor sees a healthy brain. This is an example of sampling bias.
L3 Explore data credibilityQuestion 1Which of the following are usually good data sources? Select all that apply.
Question 2To determine if a data source is cited, you should ask which of the following questions? Select all that apply.
Question 3Which of the following are qualities of a bad data source? Select all that apply.
A bad data source is not cited or vetted, is out of date or irrelevant, or solely relies on third-party information. Question 4A data analyst is analyzing sales data for the newest version of a product. They use third-party data about an older version of the product. For what reasons is this inappropriate for their analysis? Select all that apply. The data is not accurate
L4 Understand data ethics and privacyQuestion 1A data analyst uses fixed-length codes to represent data columns in order to remove personally identifying information from a dataset. What process does this scenario describe?
Question 2Data analysts never anonymize license plate numbers because that type of data can be easily seen whenever someone is out driving their car.
Question 3Before completing a survey, an individual reads information about how and why the data they provide will be used. What is this concept called?
L5 Explaining open dataQuestion 1What aspect of data ethics promotes the free access, usage, and sharing of data?
Question 2What are the main benefits of open data?
Question 3Universal participation is a standard of open data. What are the key aspects of universal participation? Select all that apply.
Weekly challenge 2Question 1Fill 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.
Question 2A 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?
Question 3Which of the following are qualities of unreliable data? Select all that apply.
Question 4In data ethics, consent gives an individual the right to know the answers to which of the following questions? Select all that apply.
In data ethics, consent gives individuals the right to know why their data is being collected, how it will be used, and how long it will be stored. Question 5An 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?
Question 6What is data privacy?
Question 7Data anonymization applies to both text and images.
Question 8The 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?
Week 3: Databases: Where data livesWhen you’re analyzing data, you’ll access much of the data from a database. It’s where data lives. In this part of the course, you’ll learn all about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also check out metadata to discover the different types and how analysts use them. Learning Objectives
Answers to week 3 quiz questionsL2 Working with databasesQuestion 1Fill in the blank: Normalized databases help avoid _ data.
Question 2What does a database’s metadata tells a data analyst about its contents? Select all that apply.
Question 3What is the difference between a primary key and a foreign key?
Question 4A data analyst at a PR firm needs to construct a database of celebrity clients. If their boss needs the data to be accessed as quickly as possible, the analyst should use a snowflake schema.
Question 5Fill in the blank: A relational database contains a series of _ that can be connected to form relationships.
L3 Managing data with metadataQuestion 1A large company has several data collections across its many departments. What kind of metadata indicates exactly how many collections the data lives in?
Question 2Fill in the blank: Data _ ensures that a company’s data assets are properly managed.
Data governance ensures that a company’s data assets are properly managed. Question 3A large metropolitan high school gives each of its students an ID number to differentiate them in its database. What kind of metadata are the ID numbers?
Question 4A company needs to merge third-party data with its own data. The company can accomplish this with which of the following actions? Select all that apply.
Question 5The date and time a database was created is an example of which kind of metadata?
Accessing different data sourcesQuestion 1A .CSV file saves data in a table format. What does .CSV stand for?
Question 2A data analyst wants to bring data from a .CSV file into a spreadsheet. This is an example of what process?
Question 3A .CSV file makes it easier for data analysts to complete which tasks? Select all that apply.
A .CSV file makes it easier for data analysts to examine a small part of a large dataset, import data to a new spreadsheet, and distinguish values from one another. L5 Sorting and filteringQuestion 1What is the process for arranging data into a meaningful order to make it easier to understand, analyze, and visualize?
Question 2Filtering by a particular criteria is an effective way to narrow the scope of a query. However, filtering is time-intensive because it can only be done one variable at a time.
Question 3A data analyst is reviewing a national database of real estate sales. They are only interested in sales of condominiums. How can the analyst narrow their scope?
Question 4A data analyst works for a rental car company. They have a spreadsheet that lists car ID numbers and the dates cars were returned. How can they sort the spreadsheet to find the most recently returned cars?
Question 5Fill in the blank: To keep a header row at the top of a spreadsheet, highlight the row and select _ from the View menu.
L6 Working with large datasets in SQLQuestion 1In MySQL, what is a proper way to write a SELECT clause starter?
Question 2Which case should be used when writing the column names in a database table?
Weekly challenge 3Question 1Primary and foreign keys are two connected identifiers within separate tables. These tables exist in what kind of database?
Question 2Metadata is data about data. What kinds of information can metadata offer about a particular dataset? Select all that apply.
Question 3Think about data as a student at a high school. In this metaphor, which of the following are examples of metadata? Select all that apply.
Question 4Think about data as a refrigerator. Which kind of metadata is the refrigerator’s product number?
Question 5What is the process that data analysts use to ensure the formal management of their company’s data assets?
Question 6Describe the key differences between a star and a snowflake schema. Select all that apply.
Question 7What are some key benefits of using external data? Select all that apply.
Question 8A 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.
Week 4: Organizing and protecting your dataGood organization skills are a big part of most types of work, and data analytics is no different. In this part of the course, you’ll learn the best practices for organizing data and keeping it secure. You’ll also learn how analysts use file naming conventions to help them keep their work organized. Learning Objectives
Answers to week 4 quiz questionsL2 Effectively organize dataQuestion 1Data analysts use guidelines to describe a file’s version, content, and date created. What are these guidelines called?
Question 2Data analysts use foldering to achieve what goals? Select all that apply.
Question 3Fill in the blank: To separate current from past work and reduce clutter, data analysts create _. This involves moving files from completed projects to a separate location.
Question 4What is the process of structuring folders broadly at the top, then breaking down those folders into more specific topics?
Question 5Successful file naming conventions include information that’s useful when trying to locate or update a file. Which of the following are effective file names? Select all that apply.
L3 Securing dataQuestion 1Fill in the blank: Data security involves using _ to protect data from unauthorized access or corruption.
Question 2When using data security measures, analysts can choose between protecting an entire spreadsheet or protecting certain cells within the spreadsheet.
Question 3What tools can data analysts use to control who can access or edit a spreadsheet? Select all that apply.
Weekly challenge 4Question 1Fill in the blank: Naming conventions are _ that describe a file’s content, creation date, or version.
Question 2A data analytics team uses data about data to indicate consistent naming conventions for a project. What type of data is involved in this scenario?
Question 3A 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.
Question 4Foldering may be used by data analysts to organize folders into what?
Question 5Data analysts use archiving to separate current from past work. What does this process involve?
Question 6Fill in the blank: Data analysts create _ to structure their folders.
Question 7A 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.
Question 8To 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.
Week 5: Optional: Engaging in the data communityHaving a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you’ll explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals. Learning Objectives
Course challengePrepare for the course challenge by reviewing terms and definitions in the glossary. Then, demonstrate your knowledge of data collection, ethics and privacy, and bias during the quiz. You will also have an opportunity to apply your skill with spreadsheet and SQL functions, as well as filtering and sorting. Finally, secure and organize data with data analytics best practices. Learning Objectives
Scenario 1, questions 1-5Question 1You’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: 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?
Question 2Next, 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?
Question 3Now, 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.
Question 4The 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.
Question 5Now 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.
Scenario 2, questions 6-10Question 6You’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. 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?
Question 7Consider 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.
Question 8Consider 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?
Question 9Next, 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?
Question 10For 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:
He asks: Which data analytics practice does this describe?
Related contentBasic Statistics Mini-Course Google Data Analytics Professional Certificate Course 1: Foundations – Cliffs Notes Google Data Analytics Professional Certificate Course 2: Ask Questions – quiz answers Google Data Analytics Professional Certificate Course 4: Process Data – quiz answers Google Data Analytics Professional Certificate Course 5: Analyze Data – quiz answers Google Data Analytics Professional Certificate Course 6: Share Data – quiz answers Google Data Analytics Professional Certificate Course 7: Data Analysis with R – quiz answers Google Data Analytics Professional Certificate Course 8: Capstone – quiz answers IT career paths – everything you need to know Back to DTI Courses Which of the following are the ways that data analyst can add context to their data?8. Which of the following are ways that data analysts can add context to their data? Select all that apply. Correct: To add context to their data, data analysts ask questions about the data, consider where it came from, and use descriptive column headers.
What is context in data analytics?Data context is the network of connections among data points. Those connections may be created as metadata or simply identified and correlated. Contextual metadata adds value, essentially making it possible to receive information from data.
What are the responsibilities of a data analyst select all that apply?A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They work in many industries, including business, finance, criminal justice, science, medicine, and government.
Which of the following tasks can data analysts do using both spreadsheets and SQL Select all that apply?Which of the following tasks can data analysts do using both spreadsheets and SQL? Select all that apply. Correct. Analysts can use SQL and spreadsheets to perform arithmetic, use formulas, and join data.
|