Research Methods & Professional Issues: Research requires a structured and disciplined approach at all stages. We'll help you to develop key research skills in many areas, from project proposals and planning to critical analysis of research findings, academic writing and presentation. We'll also ensure you consider professional standards and ethical issues in your research.
Advanced Data Management: Data management is part of any modern real-world application. We'll help you develop an understanding of data modelling, design and execution, and how to use data-driven systems and to evaluate current trends in database technologies.
Data Mining & Analytic Technologies: Many businesses rely on data mining and exploration techniques to better understand the market and customer behaviour to plan ahead and make more informed decisions. You'll learn about tools and techniques of data mining and analytics, and have an opportunity to apply them to real world problems in settings like fraud detection, customer profiling and more.
SAS Programming: The SAS Institute is a world-leading supplier of data analytics software and a partner in this Master's programme. You'll have the opportunity to discover the most popular SAS tools and development frameworks, and learn how to program using SAS 4GL language. This will familiarise you with the technologies used by major SAS customers. You'll also have a chance to earn a highly regarded, official SAS Institute Programming Certificate.
Research Project: An opportunity to complete a significant piece of self-managed research in an area that interests you. You'll engage with a complex, real-world problem where you can combine different methods and tools.
Please note that option units require minimum numbers in order to run and may change from year to year.
You'll choose two of the following units:
Business Intelligence: Vast amounts of data about a company’s customers and operations is routinely collected and stored in large corporate data warehouses. This data can be of immense value if properly analysed. You'll explore a suite of techniques and tools for data preparation and analysis, and presentation of the results to non-technical and managerial staff, in alignment with business strategies.
Analytics for Data Streams: In real world data-intensive applications, the data is arriving in a continuous stream and usually cannot be accumulated before processing. This online setting requires special techniques to analyse incoming data on the fly. Sensor networks, manufacturing industry or surveillance are just a few examples of streaming data sources. You'll learn how to efficiently process streaming data using state-of-the-art stream exploration, analysis and mining techniques.
Web Mining & Analytics: Web mining has emerged as one of the most attractive areas in applied research. It spans a large spectrum of topics such as information retrieval, topic detection and social community analysis. You'll gain extensive knowledge and systematic understanding of web and social network analysis, together with a critical awareness of current problems informed by practical experience of web modelling and mining.
- Big Data & Cloud Computing: Big data can be encountered in numerous domains and applications. Analysing large amounts of data requires special methods to cope with its volume, variety and velocity. We'll help you become familiar with methods and technologies associated with big data analytics. Cloud computing provides a secure infrastructure for systems integration, data processing and manipulation as well as storage. The cloud structure, the concept of virtualisation, services and deployment models for data storage and manipulation will be discussed.
- Optional Industrial Placement: If you take this opportunity, you'll gain experience of working in an appropriate professional environment in line with our employability strategy.
Programme specifications provide definitive records of the University's taught degrees in line with Quality Assurance Agency requirements. Every taught course leading to a BU Award has a programme specification which describes its aims, structure, content and learning outcomes, plus the teaching, learning and assessment methods used.
Download the programme specification for MSc Applied Data Analytics.
Whilst every effort is made to ensure the accuracy of the programme specification, the information is liable to change to take advantage of exciting new approaches to teaching and learning as well as developments in industry. If you have been unable to locate the programme specification for the course you are interested in, it will be available as soon as the latest version is ready. Alternatively please contact us for assistance.
The optional placement provides an excellent opportunity for you to gain first-hand industry experience and apply the learning that you have achieved through the course. The placement should be a paid job but voluntary work can be just as enjoyable.
Experience gained on the placement is invaluable in helping you to make informed decisions about your future career path, as well as enhancing your employment prospects upon graduation. Our dedicated Placements Office helps you to obtain placements and you will receive support throughout the placement experience. Interview techniques and advice are also provided to help you successfully gain a placement. A number of companies habitually accept students from this course for the placement year.
Our students have previously worked for:
- Lockheed Martin
- Sun Microsystems
- United Advertising
- British Aerospace.
International work placements
Employment prospects are now truly international and BU encourages students to consider an international work placement or volunteering experience during their degree. One way could be through the EU-funded Erasmus mobility programme which supports placements and study exchanges in Europe. Students can also participate in international placements outside of Europe. There are opportunities to engage with summer schools and volunteering projects. These experiences help students to enhance their global employability skills.
Full entry requirements
The normal requirements for embarking on this course are:
- Possession of a 2:2 Bachelors Honours degree in engineering, computing, technology, maths, physics, IT or similar, or work experience and competencies in a technical field.
If you lack the formal academic qualifications needed please contact the askBU Enquiry Service in the first instance so your application can be individually assessed.
International entry requirements
If English is not your first language, you will need to provide evidence that you can understand English to a satisfactory level. English language requirements for this course are normally:
- IELTS (academic) 6.0 overall with a minimum of 5.5 in each component, or equivalent.
View further information about our English language requirements.
A number of pre-sessional English and preparatory programmes are offered through our partner institution, Bournemouth University International College, and will get you ready for study at BU at the appropriate level.
You can also find further details of the international qualifications we accept, and what level of study they apply to, on our postgraduate entry requirements page.
The Applied Data Analytics course has been designed to address the shortage of highly qualified professionals in the intelligent computer systems industry, who are needed to harness the recent big data wave.
You will graduate this programme as a highly qualified professional, with relevant expertise and knowledge of advanced tools and technologies and the ability to understand and implement state-of-the-art solutions needed in order to address practical problems that businesses and organisations are already facing and will face in the future. This means that as a graduate of the course, you will be a highly desirable employee and enjoy a wide variety of career opportunities in a variety of industries.
Some of our Applied Data Analytics graduates are now undertaking roles such as:
- Data analyst
- Business intelligence expert
- Data manager
- Academic researcher.
Industries worked in
- Academic research.
If you want to continue your studies after achieving your Master's, you can look into our range of doctoral programmes.
Meet our staff
Dr Marcin Budka is the Programme Leader and Principal Academic in Data Science. His research interests lie machine learning, data mining, predictive modelling and computational intelligence, with a particular focus on practical applications. Marcin also has an interest in the area of complex, evolving networked systems, and practical applications for advanced predictive models.
Professor Vasilis Katos
The Head of the Department of Computing & Informatics, Vasilis is a certified Computer Hacking Forensic Investigator (CHFI) and has experience as an Information Security Consultant. He has served as an expert witness in Information Security for a criminal court in the UK.
Read more about the expertise of other members of the Department of Computing & Informatics, and register now to come along and meet some of them.
The table below indicates the latest changes to this course.
||Changes to this course
||Where the change was made
||Removal of the examination element of summative assessment from the 'Advanced Data Management' unit
Changes to the ILOs, indicative contents and reading resources to refer more explicitly to cloud computing, clarification of expected contact hours and formative assessment.