Chapter 3

Discussion Question #1: How do you describe the importance of data in analytics? Can we think about analytics without data? Explain.

Discussion Question #2: Considering the new and broad definition of business analytics, what are the main inputs and outputs to analytics continuum?

Discussion Question #3: Where do the data for business analytics come from? What are the sources and nature of those incoming data?

Discussion Question #4: What are the most common metrics that make for analytics-ready data?

Exercise #12:

Go to data.gov ! US government-sponsored data portal that has a very large number of data sets on a wide variety of topics ranging from healthcare to education, climate to public safety. Pick a topic that you are most passionate about. Go through the topic-specific information and explanation provided on the site. Explore the possibilities of downloading the data and use your favorite data visualization tool to create your own meaningful information and visualization. Show your visualization on your assignment submission.

Chapter 4

Discussion Question 1: Define data mining. Why are there many names and definitions for data mining?

Discussion Question 2: What are the main reasons for the recent popularity of data mining?

Discussion Question 3: Discuss what an organization should consider before making a decision to purchase data mining software.

Discussion Question 4: Distinguish data mining from other analytical tools and techniques.

Discussion Question 5: Discuss the main data mining methods. What are the fundamental differences among them?

Exercise #1: Visit https://www.teradata.com/University Identify case studies and white papers about data mining. Describe recent development in the field of data mining and predictive modeling.