Part 1: Carefully Review And Read Both Ends Of The Chapter A

Part 1carefully Review And Read Both End Of Chapter Application Cases

Part 1: Carefully review and read both end of chapter application cases from chapters 5 and 6 from the following required book for this class. After reading and analyzing both case studies, address all case study questions found within the case studies in scholarly detail. In addition to answering all case study questions, put yourself in these situational cases and what ideas would you have to make any operational processes or process flows better where associated in the decision-making process?

Paper For Above instruction

Part 2: Knowledge and Skills Paper

Paper Section 1: Reflection and Literature Review

Using Microsoft Word and Professional APA format, prepare a professional written paper supported with three sources of research that details what you have learned from chapters 5 and 6. This section of the paper should be a minimum of two pages.

Paper Section 2: Applied Learning Exercises

In this section of the professional paper, apply what you have learned from chapters 5 and 6 to descriptively address and answer the problems below. Important Note: Do not type the actual written problems within the paper itself.

Examine how new data-capture devices such as radio-frequency identification (RFID) tags help organizations accurately identify and segment their customers for activities such as targeted marketing. Many of these applications involve data mining.

Scan the literature and the Web and then propose five potential new data mining applications that can use the data created with RFID technology. What issues could arise if a country’s laws required such devices to be embedded in everyone’s body for a national identification system?

Survey and compare some data mining tools and vendors. Start with fairisaac.com and egain.com. Consult dmreview.com and identify some data mining products and service providers that are not mentioned in this chapter.

One of my favorites to explore is RapidMiner found at and an educational license option can be found at: Explore the Web sites of several neural network vendors, such as California Scientific Software (calsci.com), NeuralWare (neuralware.com), and Ward Systems Group (wardsystems.com), and review some of their products. Download at least two demos and install, run, and compare them. Important Note: With limited time for a college class, perfection is not expected but effort to be exposed to various tools with attempts to learn about them is critical when considering a career in information technology associated disciplines.

Important Note: There is no specific page requirement for this section of the paper but make sure any content provided fully addresses each problem.

Paper Section 3: Conclusions

After addressing the problems, conclude your paper with details on how you will use this knowledge and skills to support your professional and/or academic goals. This section of the paper should be around one page including a custom and original process flow or flow diagram to visually represent how you will apply this knowledge going forward. This customized and original flow process flow or flow diagram can be created using the “Smart Art” tools in Microsoft Word.

Paper Section 4: APA Reference Page

The three or more sources of research used to support this overall paper should be included in proper APA format in the final section of the paper.

Paper Review and Preparation to submit for Grading: Please make sure to proofread your post prior to submission. This professional paper should be well written and free of grammatical or typographical errors. Also, remember not to plagiarize!

Important Reminder: Assessment of discussion boards and other writing assignments account for 75% of overall grading and below are how grades will be assessed for this assignment:

  • Student included a minimum of “2” body pages of written content supported with “3” academic sources of research offering a detailed reflection and literature review of learning from chapters 5 and 6: 18.75 points
  • Student in scholarly detail addressed and answered all exercises or problems demonstrating application of knowledge and skills learned from chapters 5 and 6: 12.5 points
  • Student in scholarly detail offered conclusions detailing how knowledge and skills learned from chapters 5 and 6 will support continued professional and academic growth. Student also prepared process flow or flow diagrams to visualize these conclusions: 12.5 points
  • Student included a paper professionally formatted using APA and free of grammar and spelling issues: 6.25 points
  • Student successfully completed and successfully submitted this paper by the Sunday due date: 12.5 points

Total Possible Points: 62.5

References

  • Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From Data Mining to Knowledge Discovery in Databases. American Association for Artificial Intelligence.
  • Han, J., Pei, J., & Kamber, M. (2011). Data Mining: Concepts and Techniques (3rd ed.). Morgan Kaufmann.
  • Kantardzic, M. (2003). Data Mining: Concepts, Features, and Techniques. Wiley.
  • Ngai, E. W. T., Yue, T. F., & Man, M. (2012). Data Mining for Supply Chain Management: Opportunities and Challenges. Supply Chain Management: An International Journal, 17(4), 382–392.
  • Shmueli, G., Bruce, P. C., Gedeck, P., & Patel, N. R. (2020). Data Mining for Business Analytics: Concepts, Techniques, and Applications in R. Wiley.
  • Sonka, S. (1994). Knowledge Discovery and Data Mining: Concepts, Capabilities, and Challenges. Data Mining and Knowledge Discovery Technologies, IEEE Computer Society.
  • Witten, I. H., Frank, E., & Hall, M. A. (2011). Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann.
  • Xu, R., & Wunsch, D. (2005). Survey of Clustering Algorithms. IEEE Transactions on Neural Networks, 16(3), 645-678.
  • Zurko, M. E., & Simson, R. (2004). User-Centered Security: Protecting Privacy and Data in the Digital Age. IEEE Security & Privacy, 2(5), 36–44.
  • AI Multiple. (2023). Best Data Mining Tools and Software in 2023. Retrieved from https://www.aimultiple.com/data-mining-software/

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