Module 1 Challenge
Which of the following examples demonstrate data-driven decision-making?
-A hospital uses statistics in health records to identify patients who may be at risk for certain diseases. -A grocery store polls customers about their brand preferences, then uses the survey results to determine which items to stock. -A manufacturing company uses documented information about production processes to improve efficiency.
Which of the following statements correctly describe data and data analysis?
-Data is a collection of facts. -Data analysis involves collecting, transforming, and organizing data. -One goal of data analysis is to draw conclusions.
Which of the following activities are elements of data-driven decision-making?
-Figure out the business need or problem to be solved. -Ask subject-matter experts to review the results. -Find and analyze relevant data.
Which of the following scenarios demonstrate analytical thinking? Select all that apply.
-You identify and define a problem, then solve it by using data in an organized manner.
A business wants to grow its sales by 10% in the next 12 months. The data team helps achieve this goal by collecting data about current sales, their target market, and their competitors. This helps them identify the difference between where they are today and where they want to be in a year. What does this scenario describe?
Gap analysis
What is the root cause of a problem?
Why the problem occurs.
Fill in the blank: Data science is creating new ways of _________ and understanding the unknown by using raw data.
modeling
Fill in the blank: Data analysts use a ________ approach in order to identify, describe, and work out challenges or issues.
problem-oriented
A data professional working at a nonprofit prepares for a project about community forestry. They use their analytical thinking skills to determine what they want to achieve with the data. They also prioritize staying focused and on track. Which aspect of analytical thinking does this scenario describe?
Strategic thinking.
A data professional is assigned a challenging data analysis task. In order to be able to work in an orderly and logical manner, they break down larger, more complex elements into smaller pieces. Which analytical skill does this scenario describe?
Technical mindset
