Interfaculty project helps students to confront real-world issues using big data

Masters students from three different disciplines in the Faculty of Science and Engineering and the Kemmy Business School at UL have come together to work on Final Year Projects using big data.

The students from the MSc in Software Engineering, MSc in Business Analytics and MSc in Data Science and Statistical Learning presented their findings at an event held recently in the Computer Science and Information Systems building. Their presentations were a culmination of their work for the Applied Big Data and Visualisation module of their masters programmes.

Big data refers to extremely large and complex data sets that cannot be easily processed or managed with traditional data processing applications. It encompasses the collection, storage, and analysis of vast amounts of structured and unstructured data from various sources, often in real-time, to extract valuable insights and make informed decisions.

The masters students participated in a wide range of projects, covering topics including crime rate prediction, healthcare outcomes, and socio-economic dynamics. This extensive range of project topics highlights the interdisciplinary nature of big data management and visualisation.

Two projects that stood out that were excellent examples of the success of this collaborative approach were a retrospective data analysis of climate change in the Shannon Region and a deep dive into Ireland's housing crisis with future projections.   

By utilising Apache Spark and Python libraries, the students on the climate change project analysed 48 years of weather data and found insights into the local effects of climate change, which could aid in making informed decisions for environmental conservation efforts.

While the students looking at the housing crisis used extensive datasets, identifying socio-economic factors influencing housing dynamics, offering actionable insights for policymakers and stakeholders to effectively address housing challenges.

Module leader Dr. Andrew Ju praised the interdisciplinary collaboration shown in these projects and emphasised the value of diverse expertise in creating innovative solutions. He commended the students for their teamwork and dedication, recognising their remarkable achievement in delivering significant outcomes from project commencement to completion.

Congratulations to all participating groups for their excellent efforts and contributions to advancing knowledge and understanding in the field of big data management and visualisation.