Add more explanation - Very important - Cite the sources -EXTENSIVE EXPLANATION NEEDED - With your thoughts, ideas, and comments. Be substantive, and use examples to reinforce your ideas. Make sure to cite every paragraph. Make sure Your entire body of the work is cited with A---P---A ref-eren-ces, Give intro & conclusion.  introduction, subtopics, proper grammar, and a conclusion. . Be extensive; add more.

• Please use current sources from 2021 (www.google.scholar) or any Doctoral practitioner resources; don't send any explanation without citing your five ref-eren- ces or sources.

Guidance/sources:

Hou, R., Ye, X., Zaki, H. B. O., & Omar, N. A. B. (2023, March). Marketing Decision Support System Based on Data Mining Technology. Applied Sciences, 13, 4315. 10.3390/app13074315.
 

Milosevic, B., Regodic, D., & Saso, V. (2021). Big Data Management Processes in Business Intelligence Systems. Economic and Social Development: Book of Proceedings, 182-192.

Nanda, A., Gupta, S., & Vijrania, M. (2019, June). A comprehensive survey of OLAP: recent trends. In 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 425-430). 10.1109/ICECA.2019.8822203.
Özsu, M. T., & Valduriez, P. (2019). Principles of distributed database systems. Springer Nature.

Smith, J. K. (2022). Advancements in Business Intelligence Technologies: A Comprehensive Review. Journal of Business Analytics, 8(2), 123-145. https://doi.org/10.1080/12345678.2022.5678901

Walling, E., & Vaneeckhaute, C. (2020). Developing successful environmental decision support systems: Challenges and best practices. Journal of Environmental Management, 264, 110513. https://doi.org/10.1016/j.jenvman.2020.110513

Supervised learning and unsupervised learning are two machine learning methods that have both been applied by data mining techniques. Study the relevant content in the course materials and investigate the Library and Internet for information about both machine learning methods. Then, based on the results of your research, discuss the following aspects:

What are 2 or 3 applications suited to each method?
In your opinion, what is the most important issue related to each method?
Propose how to address the issues