This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.
You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.
Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.
Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.
Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.
The following modules are indicative of what you will study on this course.
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.
Graduates can expect to find employment as consultants, decision modelling or advanced data analysts, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (e.g. GlaxoSmithKline, British Airways, Santander and Unilever), public sector organisations (e.g. the NHS and primary care trusts), retail head offices, the BBC, the Civil Service, and the host of banks, brokers and regulators that make up the City, along with all the specialist support consultancies in IT and market research and forecasting, all of whom use data for the full range of decision making.
Our Work Placement Teams are based in your Faculty Registry Office and can help you find a suitable placement, as well as support you in making applications, writing CVs and improving your interview technique.
More details on work placements can be found on our Work placements page.
Visit the Business Intelligence and Analytics - Part Time (MSc) page on the University of Westminster website for more details!