March has been both a busy and interesting month in the MMA program. MMA students' deadlines for many of the final coursework deliverables happen in March. The second semester of the MMA involves building on the technical topics of the first semester by covering practical business applications of analytics. As such, we have been completing our most relevant and compelling work in the last month.
Developing predictive models
For example, as a class we have created two different financial predictive models – the first is used to predict future earnings for publicly traded firms. This was a particularly engaging task, as it can be used to develop profitable trading strategies from historical financial data. A second model was created to predict bankruptcy in publicly traded firms. This model leveraged not only financial data, but also used natural language processing (NLP) to read firm announcements, public reporting, and conference calls. While NLP itself is not a new methodology, advances in machine learning algorithms coupled with improving computing speed allow for brand new applications like this in the field of analytics.
The full life cycle of an analytics project
We have also been wrapping up several projects in our marketing course. In one term assignment, the MMA class used analytics to find and assess a market segment. A unique aspect of this assignment was that it involved not only creating a clustering model with the data obtained, but also required us to collect the data itself, through designing and distributing a survey. This gave us a more thorough appreciation about the full life cycle of an analytics project, with acquisition as the first step. In the case of a survey, the questions must be designed thoughtfully so that the underlying information may be extracted and the structure of the dataset lends itself to meaningful analysis.
Understanding the benefit of project planning in developing insight
The practicum component of the MMA is another major focus in March. With less than a month left to execute the practicum projects we began in October, we are well into the model creation and implementation phases. As any analytics professional can attest, exploratory analysis, dataset structuring, and feature selection will always take up the most time of an analytics project – these are the foundational steps. The overall value of the final insights is directly dependent on the quality of the project planning. The model creation phase in March has been the most rewarding step of the project so far, as it finally brings the practicum together and gives us a first glimpse of the results from our investigation.
Looking ahead to the end of the program, the productivity of the MMA class is accelerating. While completing the last of the coursework and executing final practicum deliverables, we are also further honing our technical skills and representing Rotman at business events and case competitions. We are looking forward to putting this experience to good use at the end of the program.
The Master of Management Analytics is designed to give students the advanced data management, analytics and communication skills needed to become an analytics professional.