CMIS 4380/MBA 5380 Business Intelligence Comprehensive Final Exam Problem – 200 points Credit Decision For this final assignment of the class you will analyze a set of credit data with a total of 425 records and 15 attributes. Here is the scenario: You are an analyst for Bear Credit Union (BCU). You have been asked by your manager to create a model to assist with the decision to determine the creditworthiness of customers. You will use the data from 400 customers (CreditRisk_Training.csv) to build your model, then you will use your model to make a recommendation on 25 customers (CreditRisk_Scoring.csv) who have applied for various types of credit. The data for those 25 customers includes an ID number that won't be used in the model (Hint: set the role of the ID number to "ID") but will be used in the results when you report who should be granted a loan. Your manager wants to use your report to impress senior management at BCU. The senior management team ("the team" from now on) has decades of banking experience but they know almost nothing about what you will be doing to conduct your analysis or how you will do it. You will prepare a report to enlighten them. Here is what your report should address: 1. (50 points) The team will want to know something about the 400 customers used as the basis for the model. Create a visualization or two that will help them understand. Use the tool of your choice and explain to the team what they are looking at and why you chose to visualize the data that way. 2. (120 points) Use the CRISP-DM model to organize your analysis. Give an overview of the CRISP-DM model, then address each of the steps in the CRISP-DM model in your report with descriptive text and screenshots (where appropriate) of your model and analysis results. Some steps will have brief coverage; some will have extensive coverage. Don't assume any prior knowledge on the part of the reader of your report – EXPLAIN EVERYTHING. Also address the following: 3. (30 points) One of the Vice Presidents has heard something about analytics but isn't sure what it means. Explain to the team what the three types of analytics are. Be sure to explain to them which type or types you are conducting in this project and why you are not conducting the other type(s).