Our MSc Big Data Analytics paves the way for you to pursue a career applying leading-edge software and analytics technology or conducting research in this vitally important field.
Every day 2.5 quintillion (2,500 followed by 15 zeros) bytes of data are created, and 90% of the data in the world today has been generated in the last two years. As a consequence, skills in identifying and obtaining intelligence from the precious commodity of big data are in demand across many sectors. On this course, you will:
Gain the technical expertise and industrial experience you need to progress your career or launch an enterprise in big data analytics
Develop high-level skills in business intelligence, data analytics and database technology
Harness the full power of SAS software, thanks to our partnership with the global leader in business analytics services
Address real-world industry-based problems and conduct a major research project on a theme of your choice
Build broader skills in communication, teamwork and management to enhance your career prospects
The course has been designed both for graduates from STEM (Science, Technology, Engineering and Mathematics) degrees, as well as subject areas where statistical analysis is a core subject, and for current professionals in Analytics and Data Science who wish to extend their knowledge and expertise of this field.
Great prospects from big data
Our MSc in Big Data Analytics gives you in-depth knowledge and critical understanding of the key issues and concepts in today’s data-driven business and science landscapes. You will develop powerful skills in the extraction, analysis and management of information from big data using a variety of scientific techniques and software tools.
This course offers the ideal introduction to knowledge discovery, analysis and assessment of data extracted from structured and unstructured big-data sets, as well as the visualisation and communication of results. You will process advanced knowledge and information, make deductions and form conclusions.
The practical skills you develop include computer modelling and the design and analysis of big data sets. You will also improve your abilities in broader areas such as communication, teamwork, management and the use of advanced quantitative methods.
Powerful industry partnerships
One of the course’s key strengths is that it is designed in conjunction with SAS, the global leaders in data analytics, whose data mining and business intelligence platform is widely used in academia and industry.
Our links with employers are also bolstered through our research and high-profile consultancy projects, ensuring that our teaching remains up to date and relevant.
Real-world learning in action
As part of your studies, you will address real-world industry-based problems during supervised computer sessions and through independent work. This intellectually demanding process requires not only specialist knowledge of big data analytics but also the ability to apply multidisciplinary concepts to today’s dynamic business and scientific areas.
Data Science Research Centre (DSRC)
Our team of computer and data science specialists are using their expertise to explore new ways of processing large sets of data to solve real-life problems.
We're in the fortunate position of having a wealth of expertise and knowledge to help tackle some of the world's greatest challenges. Take a look at examples of how we are responding to the climate emergency.
This module helps improve your ability to study at masters level and to develop, plan and execute a project using research processes. A pre-requisite for your Independent Scholarship module at the MSc stage, it enables you to review and evaluate academic literature, to gain an understanding of research design and methodological enquiry, and to systematically analyse researched data and theories.
Statistical Techniques
You will develop a rigorous understanding of statistical concepts relating to probability, data analysis and statistical modelling. The emphasis is on applying these concepts to real-life problems through the analysis of data and interpretation of results, supported by relevant software tools.
Processing Big Data
A variety of analytic methods and techniques will be discussed, including machine learning techniques, general data mining algorithms and analysis of techniques for unstructured data assessment.
You will have the opportunity to work with representative, real-world data-sets to enhance your understanding of the issues involved in managing and analysing data. You will also explore the practical aspects of data mining and management data analysis and presentation, using the SAS product set.
Analytics: Ethics, Trust and Governance
You will look at how companies can develop, deploy and manage their information analytics assets in a way that meets best practice in terms of corporate governance, information security, IT, law, corporate and information strategy, effective project delivery, ethics and ensuring a low carbon footprint.
Information Visualisation - optional module
Companies today are overwhelmed with data which is doubling in volume every 12 to 18 months. On this module you will work with high performance visualisation tools to explore new ways of dealing with this growing ‘data lake’ and ensure effective managerial action.
This is your opportunity to demonstrate your ability to apply what you have learned on the course in an independent and rigorous fashion. Through a substantial research project, you will show that you are able to formulate and tackle real business and industry problems with confidence in your technical and presentation capabilities. If you wish to consider a career in research and academia, you will find that the knowledge you have gained through this project – both theoretical foundations and technical hands-on skills – is indispensable in producing cutting-edge research for international conferences and journals alike.
Please note that our modules are subject to change - we review the content of our courses regularly, making changes where necessary to improve your experience and graduate prospects.
How you will learn
You will learn through lectures, tutorials, laboratories, individual work, seminars and presentations. Your learning will be supported by using an Internet-based repository which will hold items such as tutorial notes, supplementary reading materials and hints and tips regarding assignments.
Assessment will be provided across all modules to enable feedback at each stage and will include coursework, written exams, research projects and a dissertation/thesis.
Our teaching team
Our expert teaching team are research-active and cover a wide range of specialisms within the subject area. The teaching team includes:
Dr Ovidiu Bagdasar – Ovidiu is an Associate Professor in Mathematics. His research covers areas including optimisation, number theory, and applied/computational mathematics.
Richard Self – Richard’s area of expertise covers the broad area of governance and the issues raised by Big Data Analytics. His projects have included location services and the accuracy of GPS on smart devices, including most recently the success of Covid-19 contact tracing apps.
Professor Fatih Kurugollu – Fatih, Professor in Cyber Security, is Head of the Cyber Security Research Group (CSRG). His current research interest is around AI-based security analytics, including Big Data in Cyber Security.
The computers at the University's Visualisation Lab are equipped with the latest technologies and have industry-like capabilities to run complex analytical computations through software like Tableau, SAS, IBM Watson, Python and R Studio and Matlab.
Suntish Narain
MSc Big Data Analytics graduate
Academic named as one of the UK’s most influential technology figures
Richard, who was recently named as the country’s second most influential academic in the Tyto Tech 500 Power List, argues that the models used for analysing Covid-19 data caused delays in action taken to combat the coronavirus pandemic.
Dr Hongqing Yu also known as Harry is a Senior Lecturer in Computer Science and Programme Leader of MSc Big Data Analytics. He mainly teaches on the topics involved in Data Science, Machine learning and AI technologies.
You’ll normally need an undergraduate degree (2:2 or above) or equivalent in a science, technology, engineering or mathematics subject, or a closely related discipline with significant mathematical content
If English is not your first language, you will also need an IELTS score of 6.0 or the equivalent
Applicants without these qualifications may still be considered if they can demonstrate relevant work experience in a management or supervisory position.
Fees and funding
2022/23 Fees (August 2022 - July 2023)
Type
Full-time
Part-time
UK
£7,850 for the full course or £875 per 20 credits*
£875 per 20 credits
International
£14,700 for the full course
N/A
Please note fees normally increase in line with inflation and the University's strategic approach to fees, which is reviewed on an annual basis. The total fee you pay may therefore increase after one year of study.
* UK full-time fees paid within one academic year are rounded down to the nearest £50 if applicable
Please note at postgraduate level, you’ll need to gain the following number of credits in total to obtain the respective awards. If you have any questions please contact us.
Award
Credits
Postgraduate Certificate
60 Credits
Postgraduate Diploma
120 Credits
MA or MSc
180 Credits
This means you will gain 180 credits in total to complete the full MA or MSc. If you are studying part time you will normally complete your studies over two or three years, depending on the course structure.
Funding your studies
Find out more about fees, postgraduate loans and support you may be entitled to.
We're offering a £2,000 scholarship for all eligible international students studying a full-time postgraduate taught programme (PGT). Terms and conditions apply.
The application deadline for January 2022 starts for international students has now passed for this course. Any application you submit now will be considered for the next available start date.
As vast amounts of data continue to be generated in line with our growing use of IT products and services, exciting new career opportunities are emerging for big data specialists.
With this MSc on your CV, you will open doors to a future in many areas of computing and information technology, particularly in the areas of data analytics, business intelligence and information management, visualisation and assurance, as well as people analytics in HR.
To help you make the most of all these options, you will be well supported by the University’s careers service, who give advice on job application techniques, and by our academic staff who can provide guidance on relevant employment opportunities.
Contact us
If you need any more information from us, eg on courses, accommodation, applying, car parking, fees or funding, please contact us and we will do everything we can to help you.
Like most universities, we operate extended teaching hours at the University of Derby, so contact time with your lecturers and tutors could be anytime between 9am and 9pm. Your timetable will usually be available on the website 24 hours after enrolment on to your course.
Additional costs and optional extras
We’re committed to providing you with an outstanding learning experience. Our expert teaching, excellent facilities and great employability prepare you for your future career. As part of our commitment to you we aim to keep any additional study costs to a minimum. However, there are occasions where students may incur some additional costs.
Please also note that due to the current Covid-19 situation, if your course offers fieldtrips, the location of these may change or be cancelled. If this happens, you will be communicated to in advance and we will do our very best to seek out other practical opportunities to ensure your experience is not affected.
The information below is correct for entry in the academic year September 2021 - August 2022 only. Entry for future academic years may be subject to change.
Included in your fees
Specialist computing labs
Access to software and equipment
Mandatory costs not included in your fees
Printer consumables approx. £100 per year
Portable hard drive/memory card, approx. £120
Core textbooks, approx. £120
Portfolio case, approx. £40
Optional costs not included in your fees
Personal computer and or tablet computer. From £200 upwards depending on specification
Please note: Our courses are refreshed and updated on a regular basis. If you are thinking about transferring onto this course (into the second year for example), you should contact the programme leader for the relevant course information as modules may vary from those shown on this page.
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