Analytics for Decision Making Assignment: Data Mining Recommendations and Application

This assignment is worth 23% of the final mark for Analytics for Decision-Making. This is a group-based assignment. You should form a group of 4 members from your seminar group. Each group is required to upload a single report via your respective seminar group site in Canvas.Please elect a group leader. The responsibility of the group leader is to upload the report on behalf of the group. It is important for each group member to contribute substantially to the final submitted work. All group members are equally responsible for the entire submitted assignment. If you feel that the work distribution is inequitable to either yourself or your group mates, please highlight this to your instructor as soon as possible.

Your instructor will then investigate and decide on any action that needs to be taken. It is not necessary for all group members to be awarded the same mark. Up to 25 marks of penalties will be imposed for inappropriate or poor paraphrasing. For serious cases, they will be investigated by the examination department. More information on effective paraphrasing strategies.

Based on an organisation of your choice, recommend data mining project to help the organization in their digital transformation journey. You will need to identify a business objective that can be achieved using data mining.

(a) Define the business objective as well as the corresponding data mining objective. 

(b) Recommend an appropriate data mining technique that can be used to achieve the data mining objective in reported 1(a). 

(c) Explain how a data mining project based on the data mining objective stated in 1(a) can be implemented using the stages in CRISP-DM. Your answer should not exceed 500 words.

(d) Identify two (2) key limitation(s) of the project.

(a) Suggest three (3) charts that can be placed in a dashboard to achieve the data mining objectives proposed in Question 1. Give relevant details of each chart. 

(b) Explain how these charts can help meet the data mining objective stated in 1(a).

This final question requires you to find an article that repots a successful application of data mining in a selected industry. Give a brief summary of the selected article by discussing the following:

(i) business and data mining objective(s),

(ii) data mining technique(s),

(iii) data mining application,

(iv) how the data mining application has help to achieve the stated business objective and

(v) limitation(s) of the application.

Please provide a link to the selected article. You can refer to the case studies in the iSG as a guide. Your answer should not exceed 300 words.

(Tip: You can search for customer success stories in data mining software websites such as SAS and IBM SPSS.).Another will be allocated for your writing in terms of clarity, professionalism and organisation of the answers.