According to Wikipedia, University student retention, sometimes referred to as persistence, is of increasing importance to college administrators as they try to improve graduation rates and decrease a loss of tuition revenue from students that either drop out or transfer to another school.
Scenario: The university is interested in knowing the probability a student is likely to leave, as well as factors that drive student retention.
Data: We use student performance, biographic, engagement, and survey data. Data is kept on our staging Oracle Database, as well as in our analytic development environment. Data is versioned.
Modeling: We use a number of algorithms and pipelines, including XgBoost, Gradient Boosting, Voting Classifier, SGD, etc. and search for the best performing pipeline. Models are versioned.
Deployment: The model is exported to be used in WebFocus. Reports and Charts and Dashboards are created in WebFocus. The model can be used via Web Service (if requested).