Embark on a career in a leading-edge field and master the exciting and challenging world of big data!

Big data techniques are revolutionising how organisations and industries acquire and analyse data, offering valuable insights into how people live, work, play, travel, shop and exercise. These insights are valuable to marketers, researchers, designers, city planners, app developers, educators and many more.

GCU's MSc in Big Data Technologies helps students build the fundamental knowledge and practical skills for success in this fast-growing field. You'll develop competence in a range of emerging technologies: big data, cloud computing and the internet of things. You'll learn from the experts; GCU is internationally recognised for the strength of its research in these exciting subjects, driving 21st-century innovation.

With both full-time and part-time study available, the programme is ideal for someone with a background in computer science, software engineering, web technologies or computer engineering who wants to enhance or update their skills. Those with backgrounds in mathematics and electronics are also well suited.

The up-to-date curriculum keeps a career-focused approach, so you'll gain valuable skills you can immediately put to work in the industry.

  • Apply leading-edge tools and technologies from companies such as IBM, Microsoft and SAS
  • Explore industry-standard open-source development platforms such as Hadoop
  • Achieve industry recognition with SAS joint certification in the programme's Data Analytics module

Your expertise in big data will enable you to provide new insights into human behaviour and psychology, which can help us build stronger and happier societies across the globe. Your work could shape smart, sustainable cities; remove barriers to education; help people make healthier choices day-to-day; improve public health… and so much more. All meaningful ways of contributing to the common good.

Graduate prospects

When you graduate, you'll be a competitive candidate for roles as a systems developer, architect or administrator in data and analytics. You'll find opportunities in a diverse range of industries: engineering, pharmaceuticals, finance, healthcare, retail, security, smart environments and more.

What you will study

Full-time students complete six taught modules; three in trimester A and three in trimester B and an MSc dissertation project in trimester C. Part-time students complete six taught modules; three in Year 1, three in Year 2and an MSc project in Year 3.

Cloud Computing and Web Services

This module provides analytical and practical coverage of cloud computing and web services. It focuses on the technology, frameworks and associated standards: cloud models, cloud platforms and scalability. It also provides coverage of current web service technology and data transport representations, and integrated cloud and web service application development. Current examples of industry technology are used throughout.

Big Data Landscape

This module covers the process of managing Big Data throughout its lifecycle, from requirements through retirement. The lifecycle crosses different application systems, databases and storage media. Students will gain an understanding of the full Big Data value chain. They will be able to analyse the challenges and opportunities associated with the different stages that Big Data passes through.

Data Analytics

This module covers the basic concepts of statistics needed to understand the critical concepts of data mining, machine learning and predictive analytics used in the visualisation and analysis of data, particularly Big data. Students will gain an understanding of data preparation, the process models used in analytics, the algorithms and their requirements, the implementation of these algorithms using current technologies, and their applicability to different types of scenario. They will also gain advanced practical skills in the design, implementation and evaluation of analytical solutions to problems involving Big Data.

Big Data Platforms

This module covers the platforms that support data storage, processing and analytics in Big Data scenarios. It focuses on highly scalable platforms that provide operational capabilities for real-time, interactive processing and on platforms that provide analytical capabilities for a retrospective, complex analysis. Students will gain an advanced understanding of the principles on which these platforms are based, and their strengths, weaknesses and applicability to different types of scenario. They will also gain advanced practical skills in the design and implementation of scalable Big Data platform solutions.

Internet of Things

This module provides fundamental and practical coverage of the set of converging technologies known as the Internet of Things (IoT). It focuses on representative IoT applications, technologies, frameworks and associated standards that support and underpin IoT applications, such as sensor networks, messaging protocols, security, data storage, analytics, services and human interaction. The module provides in-depth practical coverage of representative IoT implementation frameworks including cloud-based service delivery models.

IT Professional Issues and Project Methods

This module seeks to develop understanding and practical skills in advanced project methods which are in line with industry regulations, standards and practices and are applicable to complex IT projects. The study is undertaken in an integrated fashion to ensure that the professional frameworks within which such projects are developed, deployed and managed are fully understood.

Masters Dissertation

Students will investigate a topical or emerging theme in Cloud Computing or related technologies. The dissertation acts as a vehicle for extending the knowledge and understanding of the student and the technical community in some specialist technical area. It serves its length, complexity and rigour as a suitable vehicle for extending students' range of personal, interpersonal and communication skills. In addition, it serves to develop and extend a range of high-level thinking skills, including analysing and synthesising skills and affords the opportunity for the student to demonstrate initiative and creativity in a major piece of technical work.

Entry Requirements

UK Honours degree 2:2 (or equivalent) in computing or computer engineering /electronics or cognate discipline

Other academic and vocational qualification

Each application to GCU is considered on an individual basis. If you do not have the typical academic entry qualifications, but can demonstrate relevant work experience and/or credits from recognised professional bodies, you may be eligible to enter this course via the University's Recognition of Prior Learning scheme.

  • English language
  • Academic IELTS score of 6.0 (or equivalent) with no element below 5.5.

Please note: if you are from a majority English speaking country, you may not be required to provide further proof of your English Language proficiency.

All entry requirements listed here should be used as a guide and represent the minimum required to be considered for entry. Applicants who are made a conditional offer of a place may be asked to achieve more than is stated.

Additional information

Other academic and vocational qualifications

Each application to GCU is considered on an individual basis. If you do not have the typical academic entry qualifications, but can demonstrate relevant work experience and/or credits from recognised professional bodies, you may be eligible to enter this course via the University's Recognition of Prior Learning scheme.

International pathways

If you do not meet the English language requirements, you may be eligible for the English for University Study programme.

Fees and funding

The tuition fees you pay are mostly determined by your fee status. What is my student fee status?

Tuition fees 2018/19

  • Home: £5500
  • RUK: £5500
  • EU: £5500
  • International: £12600

If you commence your studies in September 2018 or January 2019, these are the annual or module fees that apply to the duration of your course; however, fees are subject to change. For full details on how fees may change read our fees and refund policy.

Additional costs

In addition to course tuition fees, you may encounter additional costs during your time at University.


Data Lab Scholarship

The Data Lab Scholarship offers full time home or EU students full funding towards their tuition fees and also attendance at The Data Lab training events throughout the year. These are offered in conjunction with the Scottish Funding Council and European Social Fund for September 2018 entry. Scholarships will be based on academic merit, motivation and financial circumstances. Application deadline is Monday 25 June 2018. For more information visit our website.

We provide high-quality education for a fair price; as the University for the Common Good, we are committed to offering accessible higher education for talented students by keeping our tuition fees low and providing a generous scholarship package of over £2.5 million per year.

If you have any questions or enquiries regarding scholarships available for 2018/19, please feel free to contact the student enquiries team.

International student start dates

For new international students, orientation events start on 14 September 2018. This extra time is specifically designed to assist new international students in settling in the UK and GCU prior to the start of general student induction and teaching.

There will be a whole host of fun and informative activities taking place during this period, including campus and city tours, as well as welcome events where you can meet other international students.

More information is available from our award-winning Visa Immigration Support & Advice (VISA) team.

Why choose this programme?

This programme will equip students with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets. Studies on this programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cybersecurity, Internet of Things and cyber-physical systems.

Of parallel importance in our programme is to cultivate the professionalism which is expected within the industry. With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.

Work placements

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment methods

Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Program taught in:

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Last updated July 25, 2018
This course is Campus based
Start Date
1 - 2 years
5,500 GBP
Home, RUK and EU students; £12600 International students
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