Module 4 Data Management: Data Warehousing and Data Mining

Sometimes new technology can be too much of a good thing. The case for this module deals with how not to let that happen to you. While these cases are five years old, the issues are applicable now as they discuss current issues. There are four principal short readings for this Module’s Case for your to look at:

Betancourt, L. How Companies are using your Social Media Data, Retrieved on July 26, 2010 from http://www.enterpriseirregulars.com/5706/the-top-10-trends-for-2010-in-analytics-business-intelligence-and-performance-management/

Greenfield, L. (2005) The Case for Data Warehousing Retrieved Retrieved on July 26, 2010 from the World Wide Web:http://www.dwinfocenter.org/casefor.html

Greenfield, L.Greenfield, L. (2005) The Case Against Data Warehousing Retrieved Retrieved on July 26, 2010 from the World Wide Web:http://www.dwinfocenter.org/against.html

Thearling, K. (2009) An Introduction to Data Mining. Retrieved July 26, 2010 from http://www.thearling.com/dmintro/dmintro_2.htm

When you’ve familiarized yourself with the issues, then please read the following case:

Hadfield, M. (2009) Case Study: Jaeger uses data mining to reduce losses from crime and waste Retrieved Retrieved on July 26, 2010 from http://www.computerweekly.com/Articles/2009/02/23/234953/case-study-jaeger-uses-data-mining-to-reduce-losses-from-crime-and.htm

Case assignment expectations:
Use information from the modular background readings as well as any good quality resource you can find. Please cite all sources and provide a reference list (use APA format) at the end of your paper.

LENGTH: 3-5 pages typed and double-spaced.

Your answer to the following question will be assessed:

“How does one stop data warehousing and mining before they become more trouble than they are worth?”

The following items will be assessed in particular:

1.Your ability to apply your understanding of complex issues involved in the case question.

2. Your support for assertions using examples, citations (use required readings), and elaboration to support assertions. Evidence that you have read the required background materials.

3. Definition of data mining and discussion of how and when data mining can be used as a problem solving technique.

4. Description of the range of analytical tools used online or in other forms to extract meaning from the data.

5. Explanation of the role of data mining and warehousing in an organization’s overall information technology strategy

6. Description of the main data warehouse concepts.

7. Evidence of your thinking about the issues, and going beyond the obvious to develop an analysis reflecting your own critical thinking. (Note: This is discussed in Welcome Message and Module Home pages).

Case Expectations, and Grading Criteria:
Your paper will be evaluated on the following criteria (meeting minimum requirements is B performance):

_ Complete the case assignment.

_ Length of 3-5 pages (since a page is about 300 words, this is approximately 900-1500 words)

_ Conducted evaluation and analysis as required

_ Support for assertions using examples, citations (use required readings), and elaboration to support assertions. Evidence that you have read the required background materials

_ Precision: the questions asked are answered.

_ Clarity: Your answers are clear and show your good understanding of the topic.

_ Breadth and Depth: The scope covered in your paper is directly related to the questions of the assignment and the learning objectives of the module.

_ Critical thinking: It is important to read the “required readings” posted in the background material plus others you find relevant. Your paper should include important concepts from these readings and incorporate YOUR reactions and examples that illustrate your reflective judgment and good understanding of the concepts.