introduction to data analytics coursera quiz answers week 5

Practice Quiz

1. On the Data Analyst Specialist path, you could be starting your career as an Associate or Junior Data Analyst and working your way up to a Principal Analyst role. What are some of the factors that influence your growth on this path?

  • Specialization in at least one domain area
  • The experience and exposure you gain in the different areas within Data Analysis
  • A Master’s degree in either Mathematics or Statistics
  • At least five to six years of experience at each level

2. Skills such as problem-solving, communication, and storytelling are critical to the role of a Data Analyst. And like most soft skills, you’re either good at them, or you’re not; these skills cannot be acquired over time.

  • True
  • False

Graded Quiz

3. Which of the following statement describes Data Analyst Specialist Roles?

  • Analysts who advance technical, statistical, and analytical skills, over time, to expert levels
  • Analysts who specialize in data lakes and data repositories
  • Analysts who can work with Machine and Deep Learning models
  • Analysts who specialize in specific fields like HR, Sales, and Finance

4. A Principal Data Analyst is responsible for:

  • Being well-versed in Big Data processing tools
  • Having expertise in all tools and technologies used in data analytics 
  • Being a domain specialist 
  • Establishing processes in the team

5. Job roles such as Project Managers, Marketing Managers, and HR Managers, can achieve greater efficiency and effectiveness in their current roles by acquiring data analysis skills, and are therefore known as analytics-enabled job roles.

  • True
  • False

6. Which of these is essential for getting started and growing as a Data Analyst?

  • Domain specialization
  • Love for numbers, a curious mind, and openness to learn
  • A degree in Computer Science
  • A degree in Statistics

7. What Data Analysis roles may be best suited for people with little or no technical training?

  • Functional Analyst 
  • Big Data Engineer 
  • Data Analyst 
  • Data Scientist 

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