Big Data Technologies MSc

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Course Overview

UK Fees £10,500 *
International Fees £17,000 *
Alumni Discount See details
Duration 1 year

* Price per academic year

Course summary

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 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 use their big data to extract a better understanding of their customers’ needs and behaviour, to 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 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’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

 

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.

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.

Option 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.

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.

This module equips students with foundational knowledge in statistics, optimisation modelling, and operational research to enable data-driven business decision making. Students gain essential concepts in descriptive, predictive, and prescriptive analytics, applying these techniques to real-world business problems. Students analyse risk and uncertainty, evaluate analytical methods, interpret results, and communicate insights through effective writing and visualisation.

Professional accreditation

This course has been accredited by BCS, the Chartered Institute for IT, for the purposes of partially meeting the further learning academic requirement for registration as a Chartered IT Professional. The accreditation is a mark of assurance that the course meets the standards set by BCS and it entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. This course has also been accredited by BCS, on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer. The accreditation is a mark of assurance that the course meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Accreditation is valid for intakes to this course between September 2022 – August 2028.

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Programme specification

For more details on course structure, modules, teaching and assessment Download the programme specification (PDF).

To request an accessible version please email [email protected]

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Get in touch

Contact us for general course enquiries:

+44 (0)20 7911 5000 EXT 65511
(Mon-Fri, 10am-3pm GMT)

[email protected]

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(Mon-Fri, 10am-4pm GMT)

Open evenings

Join us at an open evening online or on campus. Get a feel for student life at the University of Westminster and talk to course leaders and our support teams.

Careers

This course is designed with a high degree of relevance to the industry’s needs. It will help 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.

As businesses realise the importance of data in the decision-making process, they are increasingly seeking to recruit qualified people capable of harnessing the power of data. Moreover, studies show that these jobs are some of the most difficult for employers to recruit, due, in part, to the shortage of skilled workers. 

With a growing global network of 3,000 employers, our Careers and Employability Service is here to support you to achieve your full potential.

Get yourself work-ready

This course is designed with a high degree of relevance to the industry’s needs.

Transferable skills

This course will equip you with a range of highly marketable and hands-on skills for a successful career in this industry.

Stand out from the crowd

Qualified people in big data are currently in high demand in the job market.

Job roles

This course will prepare you for roles such as:

  • AI and analytics consultant
  • Application/system developer 
  • Architect, designer and administrator of data systems
  • Big data engineer/consultant
  • Business intelligence analyst / consultant/ developer
  • Credit risk engineer
  • Data analyst
  • Data governance analyst/officer
  • Data manager
  • Data mining and business intelligence specialist
  • Data quality/compliance officer 
  • Data officer
  • Data scientist
  • Database/web application developer 
  • ETL developer/programmer 
  • OLAP programmer
  • Specialist in data acquisition, knowledge/information extraction, data analysis, data aggregation, data representation, data integration

Graduate employers

Graduates from this course have found employment at:

  • Bank of England
  • Bank-al-Etihad, Jordan
  • BCR Asigurari de Viata Vienna Insurance Group
  • Broadridge (a global Fintech company)
  • Capgemini
  • Cloudera (Hortonworks)
  • Department for Environment, Food and Rural Affairs
  • Deutsche Bank
  • Duftar (an on-demand IT services company)
  • eFinancialCareers (financial services careers recruitment web agency)
  • Esports Entertainment Group
  • Fastmarkets (Agricensus) - a cross-commodity price reporting agency in the agriculture, forest products, metals and mining, and energy transition markets
  • Financial Conduct Authority (FCA)
  • FourNet
  • Oracle
  • Veson Nautical
  • Voiceflex (a telecom carrier of SIP, hosted, connectivity, UC&C services company)

Westminster Employability Award

Employers value graduates who have invested in their personal and professional development – and our Westminster Employability Award gives you the chance to formally document and demonstrate these activities and achievements.

The award is flexible and can be completed in your own time, allowing you to choose from a set of extracurricular activities. 

Activities might include gaining experience through a part-time job or placement, signing up to a University-run scheme – such as mentoring or teaching in a school – or completing online exercises.

Read more about our Westminster Employability Award.

Westminster Employability Award

Course Leader

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.

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 6.5 in writing and no element below 6.0.

Applicants are required to submit one academic reference.

Recognition of prior learning and experience

If you have previously studied at university level, or have equivalent work experience, academic credit may be awarded towards your course at Westminster. For more information, visit our Recognition of Prior Learning page.

Application process

Visit our How to apply page for more information on:

  • the application process
  • what you need to apply
  • deadlines for applications

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 6.5 in writing and no element below 6.0.

Applicants are required to submit one academic reference.

Recognition of prior learning and experience

If you have previously studied at university level, or have equivalent work experience, academic credit may be awarded towards your course at Westminster. For more information, visit our Recognition of Prior Learning page.

Application process 

Visit our How to apply page for more information on:

  • the application process
  • what you need to apply
  • deadlines for applications

More information

What our students say

Kevin Bannon

Big Data Technologies MSc

My academic advisers have been extremely supportive during my time at Westminster. They’ve had flexible virtual “office hours” to ensure students are accommodated for when necessary. The online and in-class lectures have been complemented with tutorials where I get the opportunity to network and work alongside my classmates.

Khaled Zaghloul

Big Data Technologies MSc

For my postgraduate studies, London was an incredible city to study in. While I was still pursuing my degree, I was able to begin looking for prospective job opportunities and network with industry professionals. 

Rita Peswani Shah

Big Data Technologies MSc - 2020

I have really enjoyed learning more about Machine Learning. Before my course, I had no prior knowledge about the subject but I knew many organisations were using it. Thanks to my course, I have a clear understanding of the topic now.

Learn new skills

Volunteer and gain new skills

We offer a number of different volunteering opportunities for you to learn new skills, create connections, and make a difference in the community.

Develop your entrepreneurial skills

Our award-winning Westminster Enterprise Network offers industry networking events, workshops, one-to-one business advice and support for your start-up projects.

Get extra qualifications

We provide access to free online courses in Adobe and Microsoft Office applications, as well as thousands of specialist courses on LinkedIn Learning.

Fees and Funding

UK tuition fee: £10,500 (Price per academic year)

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.

Paying your fees

If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.

Find out more about paying your 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

There is a range of funding available that may help you fund your studies, including Student Finance England (SFE).

Find out more 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.

Find out if you qualify for one of our scholarships.

Additional costs

See what you may need to pay for separately and what you tuition fees cover.

International tuition fee: £17,000 (Price per academic year)

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.

Paying your fees

If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.

Find out more about paying your 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

There are a number of funding schemes available to help you fund your studies with us.

Find out more 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.

Find out if you qualify for one of our scholarships.

Additional costs

See what you may need to pay for separately and what you tuition fees cover.

Teaching and Assessment

Below you will find how learning time and assessment types are distributed on this course. The graphs below give an indication of what you can expect through approximate percentages, taken either from the experience of previous cohorts, or based on the standard module diet where historic course data is unavailable.  Changes to the division of learning time and assessment may be made in response to feedback and in accordance with our terms and conditions.

How you’ll be taught

Teaching methods across all our postgraduate courses focus on active student learning through lectures, seminars, workshops, problem-based and blended learning, and where appropriate practical application. Learning typically falls into two broad categories:

  • Scheduled hours: examples include lectures, seminars, practical classes, workshops, supervised time in a studio
  • Independent study: non-scheduled time in which students are expected to study independently. This may include preparation for scheduled sessions, dissertation/final project research, follow-up work, wider reading or practice, completion of assessment tasks, or revision
Year
1
13%87%
Scheduled hoursIndependent study

How you’ll be assessed

Our postgraduate courses include a variety of assessments, which typically fall into two broad categories:

  • Practical: examples include presentations, podcasts, blogs
  • Coursework: examples include essays, in-class tests, portfolios, dissertation
Year
1
6%94%
PracticalCoursework

Data from the academic year 2022/23

Supporting you

Our Student Hub is where you’ll find out about the services and support we offer, helping you get the best out of your time with us.

  • Study support — workshops, 1-2-1 support and online resources to help improve your academic and research skills
  • Personal tutors — support you in fulfilling your academic and personal potential
  • Student advice team — provide specialist advice on a range of issues including funding, benefits and visas
  • Extra-curricular activities — volunteering opportunities, sports and fitness activities, student events and more

Visit our student hub

Course location

With state-of-the-art science and psychology labs and refurbished computer suites, our Cavendish Campus offers our science and technology students a range of learning spaces that are both dynamic and inspiring,

Located in central London, our Cavendish Campus is just a five-minute walk from Oxford Street and Tottenham Court Road.

For more details, visit our Cavendish Campus page.

Contact us

Call our dedicated team on:

+44 (0)20 7911 5000 ext 65511

Opening hours (GMT): 10am–4pm Monday to Friday

[email protected]

Start live chat

Opening hours (GMT): 10am–4pm Monday to Friday

More information

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