Course Overview

UK Fees £1,100 *
International Fees £1,600 *
Alumni Discount See details
Duration 2 years

* Price per 20-credit module

Course summary

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.

Course structure

The following modules are indicative of what you will study on this course.

Core modules

The module discusses the advances that big data era has brought to the way data is used by organisations, it also considers issues related to data quality and effective data governance. You will learn about the impact the volume, velocity and variety of today’s enterprise data had to the way data is stored, managed and used, the technologies utilised in big data projects, the use of SQL and noSQL databases, Hadoop, MapReduce, Hive, etc.

A hands-on module with highly technical content, Data Repositories Principles and Tools covers the underlying technologies and approaches used in capturing, maintaining and modelling persistent data; it addresses practical issues related to data modelling and database design; finally, it provides practical/hands on skills by introducing the features and constructs of SQL.

Business Intelligence, Data Mining and Analytics are a set of methods and technologies that transform raw data into meaningful and useful information. A Data Warehouse is the architecture or structure that supports these activities. This module teaches students how to build Data Warehouses by understanding their structures and the concept of multi-dimensional modelling. The focus is on Data Warehouse design, multi-dimensional modelling, the integration of multi-source data and analysis, cloud-based data warehousing, NOSQL OLAP, aiming to support better business decision making.

The module consolidates and extends the knowledge students acquired in the taught part course, encourages and rewards individual inventiveness and application of effort. You’ll be required to carry out and bring to fruition a comprehensive piece of individual work on an approved topic (relevant to your course of studies) that involves research, planning, critical evaluation, reflection activities. To provide appropriate foundational knowledge to support the project development, the module includes a series of four blended learning workshops.

Optional modules

This module covers the theoretical and practical aspects of data visualisation including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’. Tools such as R and Tableau are used. The aim is to prepare students for becoming a data visualisation specialist.

This module explores the use of modelling to analyse and measure both online presence and impact using web and social media data. You will learn how to listen to social media conversations taking place, how such data can be transformed into actionable insight for a brand or organisation. You will also study ways in which the effectiveness of modern websites is often judged and how online web metrics can be used to drive performance. The overriding aim of the module is to equip students with the necessary technical skills and industrial knowledge for a career in the area of web or social media marketing.

This module will provide an overview of modern techniques in Machine Learning and Data Mining that are particularly customised for Data Science applications. Students will be introduced to a range of toolkits, such as R and Python and they will explore the features and strengths of different machine learning and data mining methodologies using selected data sets related to specific public sector or businesses application domains.

The module will explore how physical objects can be connected to the internet and being able to identify themselves to other devices and the role of these technology in solving a business or social problem. The module will consider the core technologies as well as the interfaces to support these systems which focuses on identifying, designing, prototyping, and presenting an IoT solution.

Cyber security threats and countermeasures at physical and digital level focusing on behaviour of employees, home users, software developers. Developments in automated threats and countermeasures.

Professional accreditation

This programme is accredited by BCS, The Chartered Institute for IT, for fully meeting the further learning educational requirement for Chartered IT Professional (CITP) status and for partially satisfying the underpinning knowledge requirements set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC) and the Science Council for Chartered or Incorporated Engineer (CEng or IEng) status. Note that there are additional requirements, including work experience, to achieve full CITP, CEng, or IEng status. Graduates of this accredited degree will also be eligible for professional membership of BCS (MBCS).

The BCS accreditation is an indicator of the programme’s quality to students and employers; it is also an important benchmark of the programme’s standard in providing high quality computing education, and commitment to developing future IT professionals that have the potential to achieve Chartered status. The programme is also likely to be recognised by other countries that are signatories to international accords.

Programme Specification

For more details on course structure and modules, and how you will be taught and assessed, see the programme specification.

Entry Requirements

A minimum of a lower second class honours degree (2:2) in IT or computing discipline, or in another discipline that either provides important underpinning for or insight into IT and computing, or it is closely related to it (e.g. sciences or engineering, business studies). If you do not have the required formal qualifications, you may be considered if you are already in employment and your role involves the use or support of the data modelling techniques and technologies covered in the course.

If your first language is not English you should have an IELTS 6.5 with at least 6.0 in writing.

Applicants are required to submit one academic reference.

View more information about our entry requirements and the application process

A minimum of a lower second class honours degree (2:2) in IT or computing discipline, or in another discipline that either provides important underpinning for or insight into IT and computing, or it is closely related to it (e.g. sciences or engineering, business studies). If you do not have the required formal qualifications, you may be considered if you are already in employment and your role involves the use or support of the data modelling techniques and technologies covered in the course.

If your first language is not English you should have an IELTS 6.5 with at least 6.0 in writing.

Applicants are required to submit one academic reference.

More information

Careers

Our Careers and Employability Service is here to support you to achieve your full potential.

With a growing network of over 3,000 employers around the world and a team of experienced careers consultants, we provide you with a variety of opportunities to work and develop new skills. As a University of Westminster student, you’ll have access to our services throughout your studies and after you graduate.

We can help you:

  • find work placements, graduate jobs or voluntary experience related to your course
  • discover international opportunities to enhance your employability
  • write effective CVs and application forms
  • develop your interview and enterprise skills
  • plan your career with our career consultants
  • gain insights into your chosen industry through mentoring
  • meet employers and explore your career options at our employer fairs, careers presentations and networking events 

Find out more about the Careers and Employability Service.

Find out more about other employability initiatives at the University of Westminster.

The course equips you with the technology knowledge and the highly sought hands on/practical skills for a successful career in big data application domains. Graduates of the programme are expected to find employment as developers, analysts, architects of big data systems, database/web application developers, data compliance officers, data quality officers, data governance officers, data governance analysts, OLAP programmers, ETL programmers and application developers, specialists in data acquisition, knowledge/information extraction, data analysis, data aggregation, data representation.

Fees and Funding

UK tuition fee: £1,100 (Price per 20-credit module)

When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.

Find out how we set our tuition fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

As well as tuition fee loans, there is a range of funding available to help you fund your studies.

Find out about postgraduate student funding options.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students, which cover all or part of your tuition fees.

Find out if you qualify for one of our scholarships.

International tuition fee: £1,600 (Price per 20-credit module)

When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.

Find out how we set our tuition fees.

Alumni discount

This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.

Funding

Find out about funding for international students.

Scholarships

The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students, which cover all or part of your tuition fees.

Find out if you qualify for one of our scholarships.

Find out more

Course Location

Our Cavendish Campus in the heart of London is home to our science and technology disciplines. With first-class facilities, the campus houses subjects from Biosciences, Computer Engineering, Nutrition and Psychology and benefits from advanced state of the art science and psychology labs. For more details, visit our Cavendish Campus page.

Contact us

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