Recent technological advances decreasing hardware costs and the ‘Internet of things’ has led to a rapid explosion in the amount of data generated in a variety of domains, including data-driven science, telecommunications, social media, large-scale e-commerce, medical records and e-health. Big data refers to the ability of exploiting these massive amounts of extremely heterogeneous in structure and content data that are routinely generated at an unprecedented scale from an ever-expanding variety of data sources. Business and industry used their big data to extract a better understanding of customers’ needs and behaviour, to develop targeted new products and to cut operational costs. The competitive advantages and productivity gains that big data brought led to a great number of a 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 the 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 will also learn through extensive course work, class presentations, group work, and the use of a range of industry standard software such as R, Python, Hadoop, MySQL, and Oracle. Assessment usually involves a combination of exams and coursework, leading to a product such as a presentation, group investigation, technical solution, a piece of software or a research review.

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