1.How do you describe the importance of data in analytics?Can we think of analytics without data? Explain.
2. Considering the new and broad definition of business analytics, what are the main inputs and outputs to the analytics continuum?
3. Where do the data for business analytics come from?What are the sources and the nature of those incoming data?
4. What are the most common metrics that make for analytics-ready data?
5. 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.
6.Define data mining. Why are there many names and definitions for data mining?
7. What are the main reasons for the recent popularity of data mining?
8. Discuss what an organization should consider before making a decision to purchase data mining software.
9. Distinguish data mining from other analytical tools and techniques.
10. Discuss the main data mining methods. What are the fundamental differences among them?
Include at least two APA formatted references (with APA in-text citations) to support the work
11.Interview administrators in your college or executives in your organization to determine how data mining, data warehousing, Online Analytics Processing (OLAP), and visualization tools could assist them in their work. Write a proposal describing your findings. Include cost estimates and benefits in your report.