Answer the following questions.

Q1) How do you describe the importance of data in analytics? Can we think of analytics without data? Explain. (150 words)

Q2) Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum? (150 words)

Q3) Where do the data for business analytics come from? What are the sources and the nature of those incoming data? (150 words)

Q4) What are the most common metrics that make for analytics-ready data? (150 words)

Q5) 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 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 visualizations. (250 words)

Q6) Define data mining. Why are there many names and definitions for data mining? (150 words)

Q7) What are the main reasons for the recent popularity of data mining? (150 words)

Q8) Discuss what an organization should consider before making a decision to purchase data mining software. (150 words)

Q9) Distinguish data mining from other analytical tools and techniques. (150 words)

Q10) Discuss the main data mining methods. What are the fundamental differences among them? (150 words)

For Questions 11 and 12 below refer to the attached case study and answer based on that.

Q11) What do you think about data mining and its implication for privacy? What is the threshold between the discovery of knowledge and infringement of privacy? (150 words)

Q12) Did Target go too far? Did it do anything illegal? What do you think Target should have done? What do you think Target should do next (quit these types of practices)? (150 words)