From book: 

Analytics, Data Science,  Artificial Intelligence Systems for Decision Support (11th Edition)

Chapter # 3

Q#1 

How do you describe the importance of data in analyt- ics? Can we think of analytics without data? Explain. 

Q#2

Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum? 

Q#3

Where do the data for business analytics come from? What are the sources and the nature of those incoming data? 

Q#4

What are the most common metrics that make for analytics-ready data? ß

Exercise#12

Go to data.gov—a U.S. government–sponsored data portal that has a very large number of data sets on a wide variety of topics ranging from healthcare to edu- cation, 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 visualizations. 

Chapter # 4

Q#1 

Define data mining. Why are there many names and definitions for data mining? 

Q#2

What are the main reasons for the recent popularity of data mining? 

Q#3

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

Q#4

Distinguish data mining from other analytical tools and techniques. 

Q#5

Discuss the main data mining methods. What are the fundamental differences among them? 

Exercise#1

Visit teradatauniversitynetwork.com. Identify case studies and white papers about data mining. Describe recent developments in the field of data mining and predictive modeling. 

I need 3 pages excluding references page and no plagiarism.