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CIS8008 Business Intelligence

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  1. apply knowledge of people, markets, finances, technology and management in a global context of business intelligence practice (data warehousing and big data architecture, data mining process, data visualisation and performance management) and resulting organisational change and understand how these apply to the implementation of business intelligence in organisation systems and business processes
  2. identify and solve complex organisational problems creatively and practically through the use of business intelligence and critically reflect on how evidence based decision making and sustainable business performance management can effectively address real-world problems
  3. comprehend and address complex ethical dilemmas that arise from evidence based decision making and business performance management
  4. communicate effectively in a clear and concise manner in written report style for senior management with the correct and appropriate acknowledgment of the main ideas presented and discussed.

Conduct an exploratory data analysis of the training data set loan-delinq.csv using RapidMiner Studio data mining tool.

(i) A screen capture of your final EDA process and briefly describe your final EDA process

(ii) Summarise the key results of your exploratory data analysis in a table named Table Results of Exploratory Data Analysis for loan-delinq.csv

(iii) Discuss the key results of your exploratory data analysis and provide a rationale for selecting your top 5 variables for predicting loan delinquency as the outcome based on the results of your exploratory data analysis and a review of the relevant literature on key factors contributing to a loan delinquency

Build a Decision Tree model for predicting loan delinquency based on the data set loan-delinq.csv using RapidMiner and an appropriate set of data mining operators and a reduced set of variables from loan-delinq.csv determined by your exploratory data analysis

(i) (1) Final Decision Tree Model process, (2) Final Decision Tree diagram, and (3) Decision tree rules.

(ii) Briefly explain your final Decision Tree Model Process, and discuss the results of the Final Decision Tree Model drawing on the key outputs (Decision Tree Diagram, Decision Tree Rules) for predicting loan delinquency. This discussion should be based on the contribution of each of the top five variables to the Final Decision Tree Model and relevant supporting literature on the interpretation of decision trees

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[Accessed 21 April 2021].

My Assignment Help. 'Business Intelligence' (My Assignment Help, 2021) <https://myassignmenthelp.com/free-samples/cis8008-business-intelligence/physicians-on-mental-health-diagnosis.html> accessed 21 April 2021.

My Assignment Help. Business Intelligence [Internet]. My Assignment Help. 2021 [cited 21 April 2021]. Available from: https://myassignmenthelp.com/free-samples/cis8008-business-intelligence/physicians-on-mental-health-diagnosis.html.

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