Course description

Every day 2.5 quintillion (2,500 followed by 15 zeros) bytes of data are created, and 90% of the data in the world today has been generated in the last two years. As a consequence, skills in identifying and obtaining intelligence from the precious commodity of big data are in demand across many sectors. On this course, you will:

• Gain the technical expertise and industrial experience you need to progress your career or launch an enterprise in big data analytics
• Develop high-level skills in business intelligence, data analytics and database technology
• Harness the full power of SAS software, thanks to our partnership with the global leader in business analytics services
• Address real-world industry-based problems and conduct a major research project on a theme of your choice
• Build broader skills in communication, teamwork and management to enhance your career prospects

The course has been designed both for graduates from STEM (Science, Technology, Engineering and Mathematics) degrees, as well as subject areas where statistical analysis is a core subject, and for current professionals in Analytics and Data Science who wish to extend their knowledge and expertise of this field

Great prospects from big data

Our MSc in Big Data Analytics gives you in-depth knowledge and critical understanding of the key issues and concepts in today’s data-driven business and science landscapes. You will develop powerful skills in the extraction, analysis and management of information from big data using a variety of scientific techniques and software tools.

This course offers the ideal introduction to knowledge discovery, analysis and assessment of data extracted from structured and unstructured big-data sets, as well as the visualisation and communication of results. You will process advanced knowledge and information, make deductions and form conclusions.

The practical skills you develop include computer modelling and the design and analysis of big data sets. You will also improve your abilities in broader areas such as communication, teamwork, management and the use of advanced quantitative methods.

Powerful industry partnerships

One of the course’s key strengths is that it is designed in conjunction with SAS, the global leaders in data analytics, whose data mining and business intelligence platform is widely used in academia and industry.

Our links with employers are also bolstered through our research and high-profile consultancy projects, ensuring that our teaching remains up to date and relevant.

Real-world learning in action

As part of your studies, you will address real-world industry-based problems during supervised computer sessions and through independent work. This intellectually demanding process requires not only specialist knowledge of big data analytics but also the ability to apply multidisciplinary concepts to today’s dynamic business and scientific areas.

How you will learn

You will learn through lectures, tutorials, laboratories, individual work, seminars and presentations. Your learning will be supported by using an Internet-based repository which will hold items such as tutorial notes, supplementary reading materials and hints and tips regarding assignments.

Assessment will be provided across all modules to enable feedback at each stage and will include coursework, written exams, research projects and a dissertation/thesis.

Our teaching team

Our expert teaching team are research-active and cover a wide range of specialisms within the subject area. The teaching team includes:

• Dr Ovidiu Bagdasar – Ovidiu is an Associate Professor in Mathematics. His research covers areas including optimisation, number theory, and applied/computational mathematics.
• Richard Self – Richard’s area of expertise covers the broad area of governance and the issues raised by Big Data Analytics. His projects have included location services and the accuracy of GPS on smart devices, including most recently the success of Covid-19 contact tracing apps.
• Professor Fatih Kurugollu – Fatih, Professor in Cyber Security, is Head of the Cyber Security Research Group (CSRG). His current research interest is around AI-based security analytics, including Big Data in Cyber Security.