Foundations: Data, Data, Everywhere - Module 1 challenge

Foundations: Data, Data, Everywhere - Module 1 challenge

  1. Which of the following statements correctly describe data and data analysis? Select all that apply.

    • Data is a collection of facts.

    • Transforming data is part of the data analysis process.

    • One goal of data analysis is to drive informed decision-making.

    • Data analysis is the creation of data.

  2. Fill in the blank: Data science involves using _____ data to create new ways of modeling and understanding the unknown.

    • raw

    • processed

    • clean

    • transformed

  3. Which of the following activities are elements of data-driven decision-making? Select all that apply.

    • Find and analyze relevant data

    • Ask subject-matter experts to review the results

    • Remove data insights that stem from human intuition

    • Figure out the business need or problem to be solved

  4. A software company wants to improve its customer experience scores by 3% over the next 30 days. A data professional works to achieve this objective by understanding current scores and how far away they are from desired scores. They then use data insights to help advance the company from where they are now to where they want to be next month. What does this scenario describe?

    • Planning

    • Future analysis

    • Guiding business decisions

    • Gap analysis

  5. Fill in the blank: Data analysts use a problem-oriented approach in order to identify, _____, and solve problems.

    • create

    • obscure

    • modify

    • describe

  6. Which of the following are examples of analytical thinking? Select all that apply.

    • Identifying and defining a problem, then solving it by using data in an organized manner

    • Considering the best graphical formats to visually communicate information

    • Noting that just because two pieces of data trend in the same direction, it does not necessarily mean they are related

    • Using intuition to drive decision-making

  7. A junior data analyst at a construction company develops a plan about a home-remodeling project. They employ analytical thinking to stay focused and on track. They also consider how to improve the quality and usefulness of the data they collect. Which aspect of analytical thinking does this scenario describe?

    • Correlation

    • Strategic thinking

    • Visualization

    • Profit-driven thinking

  8. What is the root cause of a problem?

    • A symptom of the problem

    • The impact of the problem

    • The problem’s consequences

    • Why the problem occurs

  9. A data professional is always interested in learning new skills and gaining knowledge. They often seek out challenging assignments at work and professional development experiences. Which analytical skill does this scenario describe?

    • Data design

    • Understanding context

    • Technical mindset

    • Curiosity

  10. Which of the following examples demonstrate data-driven decision-making? Select all that apply.

    • An online retailer surveys customers to develop new products that are more likely to be successful.

    • A transportation company prioritizes the preferences of local politicians when outlining routes and schedules.

    • A government agency uses facts documented in police reports to help develop crime-prevention strategies.

    • A weather forecaster refers to information about past extreme weather in order to better predict future events.