Analytics and Data Science

Unlocking the potential of data

Data is valuable. By utilising analytics we can deliver insights into health conditions, predict the weather with better accuracy, alert the authorities to crime hotspots, and show retailers what the next big trend will be. It is used to train artificial intelligence through machine learning, improving computer vision and decision-making algorithms.

But it can be hard to see the wood for the trees. When we generate so much data daily, how can you work out what is useful? If much of the data comes from specific populations and regions, how does that create biases? And do we need to give up so much digital privacy to gain the benefits of Big Data?

Academics across our university are working in data science and analytics to deliver impactful research. In the School of Mathematics, Statistics and Actuarial Science, data science has been used to improve business efficiency, discover more about how cows behaviour is impacted by ill health, and understand how biased data can affect algorithms and impact the labour market.

Our School of Life Sciences has used data to identify genes that increase the likelihood of cancer, and to understand behaviour of marine life. Academics have also used citizen science to gather data that will improve understanding of the impact of climate change on local plants, and to uncover the causes of the decrease in the duck population. The School is also working closely with the School of Computer Science and Electronic Engineering on the use of data and computer vision for monitoring crop health.

Data science doesn’t just focus on science and health. In the School of Philosophical, Historical, and Interdisciplinary Studies, researchers are creating digital datasets from physical documents, allowing easier identification of themes and trends that can unlock a better understanding of our past. Similarly, the Department of Language and Linguistics uses data to reveal dialect variations and connections between languages, for example in Africa.

Essex Law School and the Department of Sociology and Criminology have carried out projects that touch on aspects of data privacy. Open-source data can be used to track criminals or uncover human rights abuses, but biased algorithms can impact law enforcement work. The use of facial recognition technology, which requires large amounts of data for machine learning, also raises ethical considerations around privacy of both data and the individual walking on the street.

The breadth of data science means that it has many overlaps with other key areas of our research, particularly artificial intelligence, and digital health and health informatics.