Singapore University of Social Sciences

Business Analytics Applications and Issues

Business Analytics Applications and Issues (ANL310)

Synopsis

ANL310 Business Analytics Applications and Issues aims to equip students with the knowledge of various applications of business analytics in different industries. The course covers data mining applications used specifically in various industries, including fault detection in manufacturing sector, cross-selling and up-selling for service providers (for e.g., telecommunication) and customer loyalty, retention and churn in the retail sector. Towards the end of the course, issues in deployment of data mining models are also discussed.

Level: 3
Credit Units: 5
Presentation Pattern: EVERY JAN

Topics

  • Fraud Detection
  • Target Marketing
  • Model Latency
  • Oversampling
  • Product Bundling
  • Customer Segmentation
  • Churn Modeling
  • Deployment: Association versus Causality
  • Conditions for Causality
  • Placebo, Nocebo and Others
  • Alternative Explanations
  • Deployment Issues

Learning Outcome

  • Compare the different modelling techniques used in different industries
  • Describe the different data mining application used in different industries
  • Discuss issues related to the deployment of data mining models.
  • Evaluate the application of business analytics in different industries
  • Recommend the appropriate analytics techniques to derive useful information to support decision-making for a variety of business problems
  • Critique the application of business analytics in different industries
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