Big Data Technologies MSc

Recent advances in technology, along with decreasing hardware costs, led to the development and creation of smart devices and applications that pervade most aspects of daily life. The adoption and use of such technologies and applications in an ever-expanding variety of domains, including social media, entertainment, telecommunications, e-commerce, medical records and e-health, resulted in a rapid explosion in the amount and variety of generated data and to the need to store and analyse this data.

The term "big data" refers to the ability to exploit these massive amounts of extremely heterogeneous structure and content data that are routinely generated at an unprecedented scale from an ever-expanding variety of data sources. Business and industry use their big data to extract a better understanding of their customers’ needs and behaviour, develop targeted new products and cut operational costs. The competitive advantages and productivity gains that big data brought led to a great number of big data projects and a shortage of people with the required skills.

This course is aimed at people who want to move into this rapidly expanding and exciting area; it has a strong vocational flavour as it has been designed to build your knowledge and understanding of big data systems architectures and to equip you with a range of highly marketable, hands-on skills employed by the core technologies utilised in big data projects.

The course is suitable for recent graduates who wish to study for a higher qualification and/or gain technical and professional skills related to the use of big data technologies and/or data management. It's also suitable for practitioners looking to update their knowledge and technical skills in this highly prominent discipline.

The course addresses technologies, advanced theories and techniques, along with their application, implementation and integration with legacy systems. You will analyse new demands and the application of technologies in the management of data and information resources, and examine big data technologies shaping the way data is now stored and utilised including the use of cloud-stored massive datasets, distributed systems of an enterprise and how data utilisation can change and improve business processes.

Teaching approaches include lectures, tutorials, seminars and practical/hands-on sessions. You’ll also learn through extensive course work, class presentations, group work, and the use of a range of industry-standard software such as R, Python, MySQL, Oracle and noSQL databases. Modules are assessed through coursework that is practical in nature and which may involve group/individual investigations, presentations, a technical solution, a piece of software or a research review.

Top reasons to study with us

• Develop in-demand skills — ‘big data’ is a rapidly expanding area; businesses are increasingly seeking to recruit qualified people capable of harnessing the power of data
• Our course is designed with a high degree of relevance to the industry’s needs — it will help you to build your knowledge and understanding of big data systems architectures and equip you with the range of highly marketable, hands-on skills employed by the core technologies utilised in big data projects
• Master the essential software — you’ll use a range of industry-standard software such as R, Python, MySQL, Oracle and noSQL databases

Why study this course?

• Study in central London
  Based in our Cavendish Campus in central London, you’ll enjoy the benefits of studying in a major tech hub.
• Learn the fundamentals
  Learn how to analyse new demands and the application of technologies in the management of data and information resources, and examine big data technologies shaping the way data is stored and utilised.
• Prepare for industry
  You’ll use a range of industry-standard software such as R, Python, MySQL, Oracle and noSQL databases.

Professional accreditation

The programme is accredited by BCS, The Chartered Institute for IT, for partially meeting the educational requirement for CITP and CEng