The course provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into an analytics problem. The project also includes data collection & preparation, data modeling and analysis with the potential to include predictive modeling, and a solution deployment plan. Project results/ recommendations will be communicated in a report document and a final presentation.

You should submit a high-level proposal/business problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The course instructor will review the documents to confirm the scope and timing of the proposed problem and its alignment with the course requirements.

To ensure students’ learning objectives are achieved, we recommend that the datasets are large in size. Data need not be ‘clean’; it is advantageous to the students’ learning experience to require hygiene prior to analysis. Similarly, if more than one database is provided, which must be conjoined, students will be required to integrate them. This supports the learning experience and minimizes time spent on data preparation.