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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 t

he 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.
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Analytics, Data Science,  Artificial Intelligence Systems for Decisi appeared first on Assignmentio.