Industry projects can be relatively small in scope and (at a minimum) only require the affiliated organisation to provide a data set, or research problem that has been encountered and would be suitable for the students to solve.

In this course, students apply a wide range of data analytical methods and tools covered in the whole program.

Example 1: Data Visualisation project. A train link company was interested in how the on-time running of the networks can be best visualised, and where the pinch points are in the networks. Our students utilised general data visualisation and geospatial data visualisation tools to help industry partners locating the worst performing services and if some services have to be removed.

Example 2: Water Utility project. One of the largest water supply companies in Melbourne, has a yearly maintenance program for sewer reticulation cleaning including key customers and key events. The company was interested in finding out how effective these programs are, and if the frequency of blockages in these assets has come down as a result of preventative maintenance programs. Our students deciphered whether prevention programs reduce the need for responses by making use of multivariate analysis of variance techniques. Time-to-failure analyses highlighted whether prevention programs can extend the time before a failure is seen.

Example 3: Customer Segmentation for Supermarkets. One of the largest supermarket chains in Australia. Our students have built a customer segmentation model that has been used by sales to segment their fresh produce customers based on behaviour, types of products and amounts of products purchased.

Example 4: High Education Enrolment Forecast for RMIT University.

Example 5: Customer Service Improvement Using Natural Language Processing.