Big Data Analytics - MSc
The MSc Big Data Analytics course will provide you with an insight into areas of data mining, big data management, and advanced statistics. You will develop in-depth practical skills through using tools and techniques from the forefront of the emerging field of data analytics. You will use these to effectively model complex organisational requirements and propose suitable solutions....
Studying with us in 2021/22
It is possible that the 2021/22 academic year may be affected by the ongoing disruption caused by the Covid-19 pandemic. Information about the arrangements the University has put in place for the 2021/22 academic year in response to Covid-19 and the emerging variants can be found here.
Should the impact of Covid-19 continue in subsequent years of your course, any additional and/or alternative arrangements put in place by the University in response will be in accordance with the latest government public health advice, pandemic-related/health and safety legislation, and the terms and conditions of the student contract.
The MSc Big Data Analytics course will provide you with an insight into areas of data mining, big data management, and advanced statistics. You will develop in-depth practical skills through using tools and techniques from the forefront of the emerging field of data analytics. You will use these to effectively model complex organisational requirements and propose suitable solutions.
What's covered in the course?
The demand for big data analysis and management is continually increasing in business and computer science. For companies it can provide valuable insights, and results such as increased market share, profitability, possible cost savings and procedural efficiency. This course will equip you with the necessary skills to exploit big data tools and methods in order to drive innovation and growth in modern global organisations and society.
The learning activities on this Masters in Data Analytics degree are designed to encourage and facilitate your ability to gain employment and sustain a professional career in data analytics - by building your confidence and skills through hands-on experience and structured feedback. The course combines formal lectures and tutor-led workshops with independent study. You will develop key analytical and problem-solving skills, and will gain an aptitude for research, academic writing, and time management.
Technology enhanced learning will be used through the provision of online resources and discussion forums. Teaching will be conducted in a work-related context: you will work collaboratively with tutors, researchers, and businesses to prepare you for employment. Potential careers for Big Data Analytics graduates include roles in data science, data warehousing, consultancy, data security and data administration.
Tailor your degree
The Professional Placement version of the course is optional and is offered as an alternative to the standard version of the course. This will allow you to complete a credit bearing, 20 week Professional Placement as an integral part of your Master’s Degree. The purpose of the Professional Placement is to improve your employability skills which will, through the placement experience, allow you to evidence your professional skills, attitudes and behaviours at the point of entry to the postgraduate job market.
STEAMhouse is a centre for technology, innovation, creative thinking
Our brand new £70 million pound building, STEAMhouse, will become the new home for the School of Computing and Digital Technology from the start of the 2022 academic year.
This course is accredited by:
The course is very well structured and it helped me develop the skills required in the field of Data Science. The course was inclusive and involved theoretical concepts and practical real world scenarios. I enjoyed the application of Advanced Analytics, Machine Learning and Big data technologies which improved decision making and business skills. Every course module concluded with a practice assignment that allowed me to transfer the knowledge to real life learning. The faculty was extremely supportive, always approachable and very helpful in providing timely feedback and directions to sharpen my skillsets.
Why Choose Us?
Research-led, practice-driven teaching - Our teaching is underpinned by our versatile research projects and strong industry links.
Professional placement option - Gain desirable employability skills with the option of a professional placement.
Experienced academic staff - Our academic staff have extensive professional experience and are engaged with both the government and industry in helping to solve complex problems. One of our academics has been listed in the world's top one per cent of scientists in artificial intelligence and image processing.
Excellent industry partnerships - Our previous students have gained work experience and graduate roles at companies such as: Hewlett-Packard, BT, Capgemini, Cisco, IBM and more.
Committed to enhancing graduates’ employability - We support students through continuing professional development and learning in a global environment.
- Established data analytics group- which can supervise PhD projects.
- Accredited by BCS, The Chartered Institute for IT - The course meets standards set by the profession.
In order to be considered for a place on this course, you must have passed a honours degree at minimum of 2:2 or equivalent. .
Students with a business or management degree will be considered, if there has been a substantial element of computing within the degree programme.
Students who do not hold the standard entry requirements may be considered for admission provided they can demonstrate that their qualifications and/or industrial experience are equivalent.
Additional information for EU/International students
International applicants are required to have IELTS overall band of 6.0 or equivalent.
Fees & How to Apply
- UK students
- International students
Starting: Jan 2022
- Full Time
- 12 months
- £8,800 per year
- Full Time
- 18 months with Professional Placement (see below*)
- £9,700 per year
- Part Time
- 20 months
Starting: Jan 2022
- Full Time
- 18 months with Professional Placement (see below*)
- £14,520 per year
Access to computer equipment
You will require use of a laptop, and most students do prefer to have their own. However, you can borrow a laptop from the university or use one of our shared computer rooms.
You will receive £5 print credit in each year of your course, available after enrolment.
All essential field trips and associated travel costs will be included in your course fees.
Access to Microsoft Office 365
Every student at the University can download a free copy of Microsoft Office 365 to use whilst at university and for 18 months after graduation.
You will be able to download SPSS and NVivo to your home computer to support with your studies and research.
Subscriptions to key journals and websites are available through our library.
Free access to Rosetta Stone
All students can sign up to the online learning language platform for free through the Graduate+ scheme.
Media consumable items (optional)
This course requires the use of consumables.
Excess printing (optional)
Once you have spent your £5 credit, additional printing on campus costs from 5p per sheet.
All module key texts will be in the University library, but in limited numbers. You may choose to purchase a copy.
Placement expenses (optional)
If you choose to undertake a placement, you'll need to budget for accommodation and any travel costs you may incur whilst living or working away from home.
Professional Placement option*
The Professional Placement option will allow you to complete a credit bearing, 20 week Professional Placement as an integral part of your Master’s Degree. The purpose of the Professional Placement is to improve your employability skills which will, through the placement experience, allow you to evidence your professional skills, attitudes and behaviours at the point of entry to the postgraduate job market. Furthermore, by completing the Professional Placement, you will be able to develop and enhance your understanding of the professional work environment, relevant to your chosen field of study, and reflect critically on your own professional skills development within the workplace.
You will be responsible for finding and securing your own placement. The University, however, will draw on its extensive network of local, regional and national employers to support you in finding a suitable placement to complement your chosen area of study. You will also benefit from support sessions delivered by Careers+ as well as advice and guidance from your School.
Placements will only be confirmed following a competitive, employer-led selection process, therefore the University will not be able to guarantee placements for students who have registered for the ‘with Professional Placement’ course. All students who do not find a suitable placement or do not pass the competitive selection process will be automatically transferred back to the standard, non-placement version of the course.
Students are required to submit a personal statement as part of their application for this course.
Your postgraduate personal statement is going to shine a light on your personal experience, academic success, personal skills and any other factors that will support your application for further study.
Here are the key areas you’ll need to address:
Your passion and motivations
Studying a postgraduate course usually means you want to specialise in something. So what’s driving you?
Why this course?
Show that you’ve researched the course offering. What is it about this particular course that appeals to you? Is it the lecturers? The modules? Etc.
What makes you a good postgraduate candidate?
Tutors want to know that you can handle postgraduate study, so show them how your undergraduate experiences or work life has equipped you for a more advanced level of study. Key areas to address are research and group work but this can vary depending on your chosen course.
Relevant academic or work experience
Add anything relevant that relates back to your chosen course and shows how your skills will contribute towards your learning. What extra-curricular activities have you taken part in? What awards have you won? What employment or voluntary experience do you have that has helped you develop transferable skills? How do these specifically relate to the course you are applying for?
You should also mention your future plans and how a postgraduate qualification fits in. Try to look beyond your postgraduate study – do you plan to jump straight into a specific career or follow your studies with a research degree? Lastly, use plain, professional English and, where possible, utilise the language of your chosen industry.
Get more information on writing personal statements.
Course in Depth
In order to complete this course a student must successfully complete all the following CORE modules (totalling 180 credits):
As technological advances accelerate development and revolutionise the shape of our future, businesses and individuals compete ever so vigorously to maximise their efficiency. The competition involves cutting costs and making data-informed decisions. Also, the nature of data itself is evolving with the arrival of new technologies such as the Internet of Things (IoT). In fact, at its extreme, even the entire working or living environment can be treated as data: natural evolution is a well-established scientific theory that supports such a notion.
Information from data is required by many organisations and this module focuses on the application of statistical techniques to data sets primary using statistical and data analytics software. Hence a mixed learning and teaching approach is proposed that consists of both computer lab work with applying theory in practice through the use of specialist software and interactive taught sessions in a seminar room where you can work together putting theory into organisational context.
Within this module, you will gain knowledge and experience of advanced concepts of database systems and implementation techniques of database management systems. The module begins with reviewing the fundamental concepts necessary for designing, using, and implementing relational database systems. This includes conceptual design, relational modelling, Structured Query language (SQL) programming and database implementation techniques. The module then explores some of the advanced concepts of databases relevant to the role of database administrator. This includes query planning and optimization; transaction processing and concurrency control; and big data technologies. The objective is to enhance the comprehension and the advanced use of database system in order to optimize its performance. In addition, the module contains a substantial practical element utilising advanced SQL, NoSQL, enabling students to gain transferable skills in designing and developing relatively complex ‘real life’ database applications.
This module focuses on aspects of managing big data systems with respect to the five V’s (Volume, Velocity, Variety, Veracity, and Valence); i.e. systems that provide operational capabilities for realtime, interactive workloads where data is primarily captured and stored to support any analytical capabilities.
Big Data has driven the creation of new technology architectures with the likes of NoSQL, MPP databases and Hadoop that enable new types of products and services. Operational systems, such as the NoSQL databases, focus on servicing highly concurrent requests while exhibiting low latency for responses operating on highly selective access criteria.
Data mining is the non-trivial process of finding patterns and building models from data stored in data repositories such as databases and data warehouses. At the heart of Big Data Analytics and business intelligence, data mining algorithms provide readily available solutions to many Big Data problems. Data mining is an established field that provides both predictive and descriptive analytics solutions. Such solutions are often generic and can be applied to a wide range of applications from business to scientific and governmental applications.
In this module, you will be taught the internal mechanisms of developing descriptive and predictive data mining methods. Also you will be taught how to use modern data mining tools to build and numerically validate models and patterns extracted from data. You also will be able to critically evaluate current trends in data mining.
The exponential growth of social media has transformed the social, political, and technological landscapes. An increasing amount of data is generated from today’s social sites such as Twitter, Facebook, and YouTube. People use social media to publish rich content, annotate it with descriptive metadata, communicate and respond to each other. Data analytics is a powerful tool to identify trends and patterns in social media and explore how social media have been used in times of disasters, crisis or during important events such as political campaigns. This course is multidiscipline that combines social network analysis (SNA), natural language processing, and data analytics for mining social data. We aim in this course to understand an end-to-end process of social media analytics starting form data collection to extracting insights and deriving conclusions.
The purpose of the module is to enable you to undertake a sustained, in-depth and research-informed Level 7 project exploring an area that is of personal interest to you. In agreement with your supervisor, you will decide upon your topic which will take the form of a practical outcome (artefact) with accompanying contextual material. The main consideration when choosing your topic is that it must be aligned to the programme you are studying and informed by the research strategy of your school, and you should consider the relevance of this topic to your future academic or professional development.
The MSc programme is normally studied over one year full-time or two years part-time (one year and one term full-time for January start). You may move between full and part-time modes of attendance. The course is divided into taught modules of 20 credits and a Masters project of 60 credits. Students complete 60 credits for Postgraduate Certificate, 120 credits for Postgraduate Diploma and 180 credits for the full MSc. Each credit represents 10 notional hours of student learning and assessment. The structure of the course, the module, levels and credit ratings and the awards that can be gained are shown below.
A range of assessment methods are employed, assessment criteria being published in each assignment brief. Knowledge and skills are assessed, formatively and summatively, by a number of methods: coursework, examinations (seen and unseen, open and closed-book), presentations, practical assignments, vivas, online forums, podcasts and project work.
This course is accredited by the following organisations:
Our accreditations from these bodies show employers that you have the level of knowledge and skills they need when you graduate.
BCS, The Chartered Institute for IT
This degree has been accredited by BCS, The Chartered Institute for IT. Accreditation is a mark of assurance that the degree meets the standards set by BCS. An accredited degree 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. Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.
Engineering Council Accredited Degree
This degree has been accredited by BCS, The Chartered Institute for IT on behalf of the Engineering Council. Accreditation is a mark of assurance that the degree 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). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.
Enhancing your employability
This course is suitable for undergraduates and those who have worked in the industry but do not have the recognised qualifications.
The school boasts graduates who have gone on to work for Hewlett Packard, Bell Micro, Birmingham City Council, BT, Cap Gemini, Cisco, Deloitte, Ericsson, Fujitsu, IBM, Intel Corporation, NHS, Motorola, National Express, NEC, Royal Mail, Shell IT, JP Morgan Chase and Co, Carillion plc, Siemens and Nokia and many more.
The School has exceptionally strong links with industry. Collaboration with industry is at the heart of our teaching, enabling us to keep our courses relevant and up-to-date and putting you in prime position for industrial placements, chances to contribute to real-life projects and career opportunities.
OpportUNIty: Student Jobs on Campus ensures that our students are given a first opportunity to fill many part-time temporary positions within the University. This allows you to work while you study with us, fitting the job around your course commitments. By taking part in the scheme, you will gain valuable experiences and employability skills, enhancing your prospects in the job market.
It will also allow you to become more involved in University life by delivering, leading and supporting many aspects of the learning experience, from administration to research and mentoring roles.
Birmingham City University is a vibrant and multicultural university in the heart of a modern and diverse city. We welcome many international students every year – there are currently students from more than 80 countries among our student community.
The University is conveniently placed, with Birmingham International Airport nearby and first-rate transport connections to London and the rest of the UK.
Our international pages contain a wealth of information for international students who are considering applying to study here, including:
Facilities and Staff
We are constantly investing in our estate and are currently in the process of spending £340 million on new learning facilities. This course will be taught at Millennium Point at the City Centre Campus.
As a student at the School of Computing and Digital Technology, you have access to networked laboratories equipped to industry standards and running the latest software, giving you the best possible introduction to the technologies you will encounter in the world of work.
Dedicated facilities are provided for systems analysis, computer networks, programming in a wide range of languages, artificial intelligence, modelling and visual programming, e-commerce and .net environments, and business intelligence, as well as supporting the application areas of mechatronics, games technology, electronics and computer forensics.
The laboratories are well-equipped for all our computer networking courses, as well as specialist areas for practical work such as voice-over internet protocol (VoIP), forensic and ethical hacking technologies, wireless and mobile technologies and radio frequency identification technologies to name but a few.
Software development and computer programming
There are a number of open access, software development and computer programming
laboratories that can be used to develop systems and programmes, including database management systems such as MySQL, to name but a few.
Our embedded systems laboratories are used to develop real-time systems, such as specialist hardware training and development resources, and industrial-standard software development and simulation tools. These include microcontroller software and robotics design and development, to name but a few.
Electronic systemsTo underpin the basic principles of electronic systems, we have a well-equipped laboratory of general and specialist test and measurement kits, including powered prototyping development boards, dual power supplies, frequency generators and counters and digital multi-meters to name but a few.
Our successful development of forensic computing has led to a specialist forensics laboratory that is fully equipped with essential hardware and software for this sensitive area of study. The laboratory includes high-spec PC’s with built-in multi interface Tableau write blockers, EnCase and FTK computer forensic software and steganography detection and analysis software, to name but a few.
Dr Atif Azad
Reader in Evolutionary Computing and Machine Learning
Dr Azad is a Senior Fellow of Higher Education Academy. He specialises in the subject matter of Computer Science, Machine Learning, Evolutionary Computing (Genetic Programming, Genetic Algorithms, and Grammatical Evolution), Data Analytics, and Statistics.
He has extensively worked on theory and applications of Machine Learning, particularly Nature Inspired Machine Learning (Evolutionary Computing), and has conducted internationally acclaimed work winning awards and honours from recognized international scientific fora.More about Atif
Dr Jagdev Bhogal
Acting Head of Computing & Data Science Department; Associate Professor Database Systems
Jagdev is an experienced lecturer whose main teaching area is Database Systems. She is the Course Leader for MSc Business Intelligence and the MSc Big Data Analytics courses. Jagdev has published conference and journal papers on relational/object/nosql database systems, ontologies, text mining and cloud computing.More about Jagdev
Besher is an accomplished software engineer with over eight years of experience in data analysis and information management. He holds a BSc in Software Engineering and a Master's degree in Business Intelligence. Besher's career so far has seen him work for various international organisations and UN agencies, as well as developing many information management products, using cutting-edge tools and technologies.More about Besher
Dr Iain Rice
Dr Rice is a specialist in Machine Learning and Signal Processing with several years of experience applying AI models to a wide range of real-world problems. As the head data scientist for The RAPID Project Iain created algorithms allowing for up to 12 hours advanced prediction of cardiac arrest in children.
Iain has taught on several computational and mathematical programmes at both traditional and distance learning universities. As the course leader for the MSc Artificial Intelligence he is passionate about seeing everyone learn more about AI and mathematics, especially those from a non-computing background.
Iain’s PhD was in the area of applied mathematics where he worked with Thales (UK) Ltd, a defence contractor, to analyse SONAR data. He created visual informatics capable of inferring anomalies in a complex environment. Whilst working on this problem he created a novel computational architecture capable of outperforming standard Deep Learning models and is a self-proclaimed ‘deep learning sceptic’.
Dr Rice is open for applications of self-funded PhD projects, MSc research projects, industry collaborations and general academic partnerships pertaining to applied Machine Learning and data-driven challenges.More about Iain
Hossein is a PhD student and a Visiting Lecturer in the Cloud Computing department at Birmingham City University. His supervisor is Mohamed Gaber and his doctoral research goal is to propose an evolutionary approach to cope with different concept drifts in non-stationary data streams. Hossein holds a Master's degree in computer engineering from the University of Tehran, Iran, where his thesis looked into developing a framework for tag-based social image search based on textual and visual features. He also holds a BSc computer engineering degree from the University of Ahvaz, also in Iran.
Prior to his PhD study, Hossein has worked as a senior technical support engineer in the telecommunication industry for more than a year. He also worked as a website designer/developer for around two years.More about Hossein
Dr Daniel Doolan
Dr. Doolan is a Senior Lecturer in Software Engineering and has been working in the University sector for over a dozen years having published over fifty research articles primarily in the domain of mobile computing. He holds a PhD in Computer Science with a focus on Mobile Computer Graphics and the application of Parallel Computing to the mobile domain. His master’s research examined the use of fractals in multimedia applications, specifically for 2D-4D image generation, compression and data encryption.
His main research interest is mobile computing, graphics and multimodal interaction, collaboration context awareness and the sensing of the surrounding environment.
His postgraduate work was undertaken at University College Cork known throughout the world for the pivotal work of Professor George Boole, the “father of the information age” upon which the entire worlds computing hardware and software is based. Visit georgeboole.com to find out more about his 2015 bicentenary celebrations.
Dr. Doolan has previously held the roles of Director of Studies & Course Leader for a 5 year BSc (Hons) Computer Science degree programme, Research Degree Coordinator and Research Seminar Coordinator having organised and hosted over eighty seminars in recent years.
He has written regularly about computing & his teaching – a summary of which is available on Dr. Doolan’s Website (University Related Posts).More about Daniel