Data mining

1.Define data mining and why it is important to business organizations.
2.Data mining is at the intersection of many disciplines. Please list 7 of those disciplines.
3.Describe structured and unstructured data. Please give examples of each.
4.A major objective in data mining is to extract patterns from data. Explain what a data pattern is, and list 4 types of patterns related to data mining.
5.Discuss at least 3 industries where data mining is used and how data mining can help companies in those industries.
6.Explain the 6 steps in the CRISP Data Mining Process.
7.Describe the 4 ways data should be prepared before being used for data mining.
8.Discuss the SEMMA Data Mining Process.
9.Describe the Classification data mining method.What are some of the methodologies and techniques used for the Classification method?
10.Discuss Cluster Analysis in terms of how it’s results may be used, and some of the analysis methods used.
11.Describe Association Rule Mining. How can it be used in business?
12.What is meant by Supervised and Unsupervised learning methods?

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