Big Data (Extended International) MSc
  • Research-informed teaching that has direct value to industry, commerce and to you as an IT industry professional.
  • You will develop a critical perspective of Big Data and be able to apply this to a range of scenarios
  • Access to a wide range of facilities, including laboratories housing specialist computing equipment and software

The modern world is experiencing a growth of online data in a variety of forms, including social networks, web documents, digital libraries, blogs, medical records, biological data, remote sensing, imaging, forecasting etc. This data may not be fully structured but still contains valuable information that needs discovering, such as emerging opinions in social networks, consumer purchase behaviour, trends from search engines, and other patterns that emerge from such huge data sources.

These developments mean traditional applications are no longer appropriate to the processing and analysis of the amount of data available. Companies, such as Google, are leading the movement from a large-scale relational database reflecting the desire to analyse data automatically and on a larger scale than previously seen.

Course content

The Extended learning route offers extra modules on employability, and study skills including writing in English accommodating the needs of Interntional students who initially require additional support in these areas. You will study common core modules in your first semester with other students on Computing extended awards before specialising.

The course is designed to respond to critical skill shortages in the rapidly expanding field of Big Data. It offers a balance of practical skills combined with academic rigour in the field of Big Data. This is a unique offering which builds on the strengths and experience of Staffordshire University in delivering practical scholarship relevant to real world situations.

It is intended to assist students and career professionals enter and succeed in the growing, high demand analytics workforce.

As a full time student, you would study in the first specialist semester:

Managing Emerging Technologies COIS71170

Data Harvesting and Data Mining COIS71171

Distributed Storage COIS71172

Distributed Processing COIS71173

This first semester is concerned with those areas of big data fundamentals and is used to examine how big data is stored, processed and how an organisation can start to use tools to examine this data and start to improve businesses awareness of its customer base.

In the second semester you will study

Research Methods COIS71040

Virtualisation COCS70665

Big Data Applications COIS71174

Data Modelling and Analysis COIS71175

This semester encompasses a module on how to manage big data within a network, a maths module on algorithms that are required to enhance big data and a module which will prepare you for the master project in the last semester. The last module will examine existing big data applications that can help get the most out of big data.

The final semester is a major research project. The actual content is open to discussion with the award leader and project supervisor must be a discipline related to Big Data.

On completion of the award you will have developed detailed knowledge and understanding of Big Data and the ability to apply this knowledge in an academic or commercial context.

The award also aims to instil sound academic & professional skills required for lifelong learning & development - for example, skills in research methods, critical thinking & analysis, academic and professional report writing, and communication skills.

MSc Award
January, September Start
Full-time Study Mode
2 years Duration

Entry Requirements For This Course

Normal requirements are at least a UK second class honours degree or equivalent in a related computing discipline
If you do not meet the above but have significant appropriate experience, your application will be considered, provided that you satisfy the University that you are capable of responding to the challenge of postgraduate work.
If your first language is not English, you will need to demonstrate that you are fluent enough to cope with the course. A minimum score of IELTS 6 or TOEFL 550 (213 computer-based) is normally required.

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