Course Overview

Attendance
UK/EU Fees £9,500 *
International Fees £13,500 *
Alumni Discount See details
Duration 1 year

* Price per academic year

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.

The project module plays a unifying role, it aims to encourage and reward individual inventiveness and application of effort. It is an exercise that may take a variety of forms and which provides you with the experience of planning and bringing to fruition a major piece of individual work. The scope of the project is not only to complete a well-defined piece of work in a professional manner, but also to place the work into the context of the current state of the art in big data Technologies/ Business Intelligence and/or Analytics/Business Systems Design and Integration.

A hands-on module with highly technical content, it 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.

This module covers 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. You will learn how to build data warehouses by understanding their structures and the concept of multi-dimensional modelling. You will also learn about the recent technological developments in integrating and analysing large amounts of business data. The aim is to equip students with the skills and industrial knowledge for a career as a Data Warehouse developer, OLAP programmers, ETL programmers and application developers, specialists in data aggregation.

This module aims to develop and strengthen your core skills around professionalism and research. It covers research-related issues such as critical evaluation, gathering and analysing information, preparation and planning of projects. It also covers methods/approaches applicable to complex IT projects, which are in line with industry regulations, standards and practices, including those related to professional, legal, social and ethical issues. The module will equip you with valuable skills for your university studies and your future career development.

Optional modules

The module covers the whole data lifecycle from creating to processing data and from publishing and to preserving data. You will learn how to use advanced big data analytics approaches and about the latest research advances and technology trends in relation to the use of big data analytics. Cutting edge big data analytics case studies will be utilised to build up your capabilities and skills to analyse existing solutions, and to select and design the most suitable solution for enterprises. Big data analytics technologies, such as Hadoop, MapReduce, Hive, etc. are used.

The module will build your theoretical understanding of issues related to the provision of IT resources and services based on the cloud computing paradigm, and how this new IT provisioning model can be utilised in enterprise and business computing. The aim is to equip you with the knowledge and skills to analyse different cloud computing solutions, and to design and select the most suitable such solution for a business. You will also develop hands-on experience utilising cutting edge cloud computing solutions for solving business related problems.

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 develop your theoretical and practical knowledge of the W3C; you will also learn how to design, implement dynamic web pages/applications capable of interaction with databases, to critically evaluate sophisticated server-side applications and to develop a user interface for the Web application using appropriate software tools, e.g. cascading style sheets, HTML4/5, JavaScript and/or an application development suit. The aim is to equip you with skills required to analyse, evaluate and implement web-based business applications and to prepare you for a career in the area of database/web application development.

You may take instead another postgraduate module in the Department, at the course leader’s discretion.

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.

Entry Requirements

You are expected to have some basic exposure to technologies employed by modern and data-driven business applications, with an interest in developing further skills and knowledge to support postgraduate activity in relation to data science, big data, and/or data management technologies on a range of real-world data-driven problems. You will have a good Honours degree (at least a Lower Second) from a UK university (or overseas equivalent) in an 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 will also need an IELTS score of at least 6.5, with 6.0 or above in each test component, or equivalent.

View more information about our entry requirements and the application process

 

 

You are expected to have some basic exposure to technologies employed by modern and data-driven business applications, with an interest in developing further skills and knowledge to support postgraduate activity in relation to data science, big data, and/or data management technologies on a range of real-world data-driven problems. You will have a good Honours degree (at least a Lower Second) from a UK university (or overseas equivalent) in an 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 will also need an IELTS score of at least 6.5, with 6.0 or above in each test component, or equivalent.

More information

Careers

Our Career Development Centre has just been shortlisted for the Best University Careers Service in the National Undergraduate Employability Awards for 2017.

With a growing network of over 3,000 employers around the world and a team of experienced careers consultants, we are here to help you succeed.

In 2015–16, we helped over 1,500 students find work placements across a range of sectors, with 250 employers attending 14 on-campus skills and careers fairs.

As a Westminster student, you’ll have access to our services throughout your studies and after you graduate.

We can help you:

  • find work placements related to your course
  • find part-time/vacation, placement and graduate jobs, including voluntary experience
  • find international opportunities to enhance your employability
  • market yourself effectively to employers
  • write better CVs and application forms
  • develop your interview and enterprise skills
  • plan your career with our careers consultants
  • meet employers and explore your career options at our employer fairs, careers presentations and networking events throughout the year

Find out more about the Career Development Centre.

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 and EU tuition fee: £9,500 (Price per academic 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 undergraduate students, which cover all or part of your tuition fees.

Find out if you qualify for one of our scholarships.

International tuition fee: £13,500 (Price per academic 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 undergraduate 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 the Faculty of Science and Technology. With first-class facilities, the campus houses subject areas ranging from biosciences to electronic engineering. For more details, visit our Cavendish Campus page.

Contact us

Call our dedicated team on:

+44 (0)20 7915 5511

Opening hours (GMT): 9am-5pm Monday to Friday

[email protected]

More information

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