Google Data Analytics Capstone: Complete a Case Study Quiz Answers

All Week Google Data Analytics Capstone: Complete a Case Study Quiz Answers

Google Data Analytics Capstone: Complete a Case Study Quiz Answers

Test your knowledge of professional case studies

Q1. Fill in the blank: A _____ is a collection of case studies that you can share with potential employers.

  • personal website
  • portfolio
  • problem statement
  • capstone

Q2. Which of the following are important strategies when completing a case study? Select all that apply.

  • Document the steps you’ve taken to reach your conclusion
  • Answer the question being asked
  • Use a programming language
  • Communicate the assumptions you made about the data

Q3. To successfully complete a case study, your answer to the question the case study asks has to be perfect.

  • True
  • False

Q4. Which of the following are qualities of the best portfolios for a junior data analyst? Select all that apply.

  • Large
  • Simple
  • Personal
  • Unique

Q5. Which of the following are places where you can store and share your portfolio? Select all that apply.

  • RStudio
  • GitHub
  • Tableau
  • Kaggle

Test your knowledge by completing a case study

Q1. For the following six questions, consider your detailed case study report and the steps of the data analysis process that you followed when creating it: ask, prepare, process, analyze, share, and act.

In the ask phase of your analysis, you wrote a clear statement of the business task. According to the Case Study Roadmap, this statement should 1) identify the specific problem you are trying to solve, and 2) consider key stakeholders. Take a moment to review your statement now. In what ways could you make it more effective at meeting these two requirements?

  • Comment Correct Answer Below

Q2. In the preparation phase of your analysis, you described the data sources you used. According to the Case Study Roadmap, this description should include where the data is located and how it is organized. It should also consider issues with bias or credibility, problems with the data, and how you verified its integrity. Finally, your description should explain how the data helped you answer your questions. Take a moment to review your description now. What steps could you take to make it even more descriptive?

  • Comment Correct Answer Below

Q3. In the process phase of your analysis, you documented your data cleaning and manipulation. According to the Case Study Roadmap, this documentation should include a list of the tools you used and why you selected them. In addition, it was an opportunity to explain how you ensured your data’s integrity and confirmed that it was clean and ready to analyze. Take a moment to review your documentation now. How can you improve it in order to describe your cleaning and manipulation techniques even more thoroughly?

  • Comment Correct Answer Below

Q4. In the analysis phase of your analysis, you wrote a summary of your analysis. According to the Case Study Roadmap, this summary should discuss organizing and formatting your data. In addition, it should detail any surprises, trends, or relationships you discovered. Lastly, you should summarize how these insights helped you answer your questions. Take a moment to review your summary now. How can you improve it in order to highlight your analysis process in a more compelling way?

  • Comment Correct Answer Below

Q5.In the sharing phase of your analysis, you created data visualizations to support your key findings. According to the Case Study Roadmap, these visualizations should reflect your findings, data story, and audience — while keeping accessibility top of mind. Take a moment to review your visualizations now. Which one are you most proud of? And how can you apply your experiences during this course in order to improve the others?

  • Comment Correct Answer Below

Q6. In the act phase of your analysis, you provided recommendations based on the final conclusion from your analysis. You were also asked what additional data you could analyze to enhance your work. Take a moment to consider this question again now. Respond with at least two ideas that you did not include in your original report.

  • Comment Correct Answer Below

Test your knowledge of effective interview techniques

Q1. An elevator pitch gives potential employers a quick, high-level understanding of your professional experience. What are the key considerations when creating an elevator pitch? Select all that apply.

  • Focus on your process over the results
  • Consider your audience’s interests
  • Make sure it’s short enough that it can be explained to someone during an elevator ride
  • Keep it fresh by not over-practicing it

Q2. What are the key purposes of discussing a case study during an interview? Select all that apply.

  • Negotiate a fair salary for the position
  • Recommend real-world solutions based on your own work
  • Ask your potential employer questions about the company
  • Outline your thinking about a data analytics scenario for your interviewer

Q3. If an interviewer says, “Tell me about yourself,” it’s important to limit your response to topics related to data analytics.

  • True
  • False

Q4. During an interview, you will likely respond to technical questions, practical knowledge questions, and questions about your personal experiences. What strategies can help you prepare to respond effectively? Select all that apply.

  • Copy real-world examples from more experienced professionals to include in your responses
  • Practice your responses until they feel natural and unrehearsed
  • Brainstorm examples from your own experiences that support your answers
  • Write down your answers to common questions

Q5. Imagine that an interviewer asks, “How do you maintain data integrity?” What topics does this question give you the opportunity to discuss? Select all that apply.

  • The importance of reliability and accuracy in good data analysis
  • The impact that issues with your data can have on business decisions
  • The methods you would use for error checking and data validation
  • The reasons you strongly preference SQL over spreadsheets for data cleaning

<< Previous Course Quiz Answers

Data Analysis with R Programming

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

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We are Team Networking Funda, a group of passionate authors and networking enthusiasts committed to sharing our expertise and experiences in networking and team building. With backgrounds in Data Science, Information Technology, Health, and Business Marketing, we bring diverse perspectives and insights to help you navigate the challenges and opportunities of professional networking and teamwork.

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