(MSc) Master of Science
Business Analytics
Current
University of Essex
University of Essex
Essex Business School
Southend Campus
Masters
Full-time
MSC N111JS
10/05/2023
Details
Professional accreditation
None
Admission criteria
A 2:2 degree, or international equivalent, in one of the following subjects: Engineering Science, Computer Science, Economics, Statistics, Finance, Accounting, Information Systems or Business Analytics.
We will also consider a degree in any discipline, which includes at least one of the following modules:
- Statistics, Economic Statistics, Probability or Biostatistics
- Quantitative methods or Quantitative analysis
- Engineering Maths, Advanced Maths, Applied Maths, Pure Maths, Calculus or Mathematical methods
- Management Science
- Operations Research
We will also consider applicants with a lower level degree on a case by case basis
with relevant work experience.
IELTS (International English Language Testing System) code
IELTS 6.5 overall with a minimum component score of 5.5
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
Additional Notes
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Course qualifiers
A course qualifier is a bracketed addition to your course title to denote a specialisation or pathway that you have achieved via the completion of specific modules during your course. The
specific module requirements for each qualifier title are noted below. Eligibility for any selected qualifier will be determined by the department and confirmed by the final year Board of
Examiners. If the required modules are not successfully completed, your course title will remain as described above without any bracketed addition. Selection of a course qualifier is
optional and student can register preferences or opt-out via Online Module Enrolment (eNROL).
None
Rules of assessment
Rules of assessment are the rules, principles and frameworks which the University uses to calculate your course progression and final results.
Additional notes
None
External examiners
Dr Ping Zheng
Canterbury Christ Church University
Prof Wantao Yu
Professor of Supply Chain Management
University of Roehampton
External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment.
External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course.
They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards.
External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.
Programme aims
- To develop students’ knowledge about the importance of business analytics in enhancing performance of diverse business functions;
- To enable students develop critical, indepth and systematic understanding and evaluation of the study and practice of business analytics and management for effective decision making in diverse business contexts;
- To develop students’ theoretical and practical understandings and skills in a range of data analytics, simulation based and statistical techniques and tools;
- To equip students with necessary numeric, analytical and problem solving skills to successfully implement business analytics for decision making purposes in a business context;
- To develop students’ ability in acquiring, organizing, integrating, analyzing and interpreting big data in order to generate business insights and intelligence, and make accurate forecasts about diverse decision scenarios and outcomes;
- To help students develop a systematic understanding of the organisational and external contexts in order to better inform business analytics practice;
- To equip students with skills to manage their own learning, learn to work in teams, and network and communicate with different stakeholders;
- To prepare students for rewarding careers as business analysts, managers or consultants in different types of organisations in the private and public sector;
- To help students acquire the skills for successfully conducting independent research practice and help them gain foundation for pursuing further academic study (i.e. PhD degree).
Learning outcomes and learning, teaching and assessment methods
On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:
A: Knowledge and understanding
A1: Developing a critical and systematic understanding of diverse types of business processes and decisions such as innovation and R&D, production and supply chain, and market extension.
A2: A comprehensive understanding of the internal and external environmental factors affecting the performance of different business management decisions.
A3: Developing in-depth and critical insights into the role and potential of business analytics in solving complex real life problems, and supporting strategic and tactical decision making in a business context.
A4: A theoretical (i.e. research led) and practical understanding of diverse data analytics, statistical, simulation based, and managerial decision making methods and approaches which will allow students to evaluate and critique existing research (i.e. theoretical and methodological) and business practice in business analytics.
A5: An analytical and systematic understanding of applying a range of data analytics, statistical and simulation based techniques and tools to solve complex business problems and give sound business decisions.
A6: Developing essential knowledge and skills to acquire and analyze big data and information, to evaluate their relevance, reliability and validity, and to synthesise a range of data and information for different research purposes and new situations.
A7: Developing essential understanding and ability in conducting independent and original research in the area of business analytics, and skills in clearly communicating a research output to diverse types of audiences.
Learning methods
Learning methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Lectures, tutor-led seminars, lab based exercises and workshops;
Essential and recommended directed reading of textbooks, peer reviewed journal articles, business case studies, business newspapers and periodicals on different aspects of business analytics and economics to develop students’ knowledge and understanding on the subject matter;
Lab based data analytics, simulation and other statistical data analysis exercises using freely available datasets, web analytics services (e.g. Google Analytics, Google BigQuery, Tableau Public) and established analytical tools (e.g. R, S-Plus, Spotfire, SPSS for statistics, Netlogo, and Excel) to enable students to understand how to use diverse techniques and toolkits for business analytics purposes, and develop their numeracy knowledge and skills;
Formal formative assessment which will consist of hands on practical coursework (e.g. application of data analytics, simulation and statistical techniques); individual assignments, group work assignments and oral presentations. Related feedback, coupled with peer group interaction would enable students to augment their understanding of the topics;
Informal assessment will be made in seminars through peer group and in class discussions, and oral presentations to enable students to successfully comprehend the subject matters;
Discussions and interactions with industry invited as guest speakers; networking with external communities of practice to enhance practical knowledge and understanding of students;
Lectures and directed self-study for the identification of different research paradigms, techniques and methods used in academic dissertation, and those which can be used to inform and support practical scenarios; and
Self directed study with supervision.
Assessment methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Learning outcomes A1 to A6 will be formally assessed by individual and group coursework (i.e. reports), written dissertation proposal and written examinations;
Learning outcomes A1 to A4 will be formally assessed by group presentations;
Learning Outcomes A1 to A6 will be informally assessed via lecture and seminar activities and discussions;
Learning Outcomes A3 to A6 will also be informally assessed by lab based exercises and one-to-one discussions with lecturers during consultation hours; and
In addition, the dissertation project (where completed) will assess learning outcomes A6 and A7.
B: Intellectual and cognitive skills
B1: Critically reviewing and evaluating theories and empirical evidence in the area of business analytics and management, synthesising different ideas and perspectives, proposing new arguments and hypotheses, and communicating ideas, arguments and knowledge effectively, in a clear and coherent manner.
Critically reviewing and evaluating theories and empirical evidence in the area of business analytics and management, synthesising different ideas and perspectives, proposing new arguments and hypotheses, and communicating ideas, arguments and knowledge effectively, in a clear and coherent manner.
B2: Developing skills in analysing, evaluating and forecasting potential implications of internal and external environmental factors in the performance of diverse business operations and decisions.
B3: Planning, carrying out and managing independent and original research.
B4: Synthesising, analysing and evaluating different sources of information and data (i.e. big data) to most effectively solve complex real life problems, to undertake forward planning and to give sound business decisions.
B5: Application of numeric and analytical knowledge and skills in finding alternative solutions for different decision scenarios.
Learning methods
Learning methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Lectures and seminars; active learning processes such as lab exercises, preparation of individual and team-based analytical courseworks, presentations of assignments to assessment panel, written examinations and inclass discussions which will help students to develop their intellectual and cognitive skills such as critical, analytical, synthesising, problem solving and decision making skills;
Essential and recommended directed readings from different sources of information which will enable students to synthesise and evaluate divserse types of knowledge. They will also ensure students to develop a critical awareness of current issues in business analytics and economics informed by leading edge research and practice in the subject field;
Written examinations and problem based, analytical exercises and group assessments which will help students to learn how to deal with complex issues and solve problems systematically and creatively. Independent coursework, research proposal and dissertation project which will be used to enhance intellectual skills related to specialist knowledge, understanding and practical skills of students. These assessment menthods will also ensure that students can evaluate and integrate theory and practice in a variety of situations. Such methods and strategies will be built into each module of the programme; and
Self-directed dissertation project with dedicated supervision which will help students to learn how to act autonomously in planning and implementing a research project, and develop an original and creative piece of work;
Assessment methods
Assessment methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Learning outcomes B1 to B5 will be formally assessed by written individual and group coursework, and written examinations;
Learning outcomes B1 and B2 will be formally assessed by the presentations of group work;
Learning outcomes B1, B2, B4 and B5 will also be informally assessed via lecture and seminar activities and discussions, informal feedback about lab based exercises, and one-to-one discussions with lecturers during consultation hours; and
In addition, the dissertation project (where completed) will assess learning outcome B3.
C: Practical skills
C1: Oral and written communication skills.
C2: Ability to acquire, organise, integrate, analyse and interpret big data in order to generate valuable insights into business intelligence and decision making.
C3: Development of practical knowledge and skills in solving complex real life problems using a range of data analytics, simulation based and statistical techniques and tools.
C4: Use information technology, such as word processing, spreadsheets, databases, data analytics and simulation based technologies and tools, statistical and web-based packages to read, synthesise data and information in order to support research practice, problem solving and decision making.
Learning methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Discussions of examples and cases from business practice during lectures and seminars which will help students to develop skills in applying theoretical knowledge to solve practice based problems;
Lab based data analytics, simulation and other statistical analysis exercises which will develop practical skills of students including ability to analyse, solve problems and make decisions on diverse business matters and enable students to demonstrate and communicate their results.
Written materials and manuals provided to students will help them to improve their knowledge and skills in using a range of data analytics, simulation and statistical data analysis software and toolkits in order to address practice based problems;
Discussions and interactions with industry invited as guest speakers; networking with external communities of practice to enhance external awareness of students (e.g. knowledge of work, organizational cultures, business skills), to provide an informal means for the assessment of their practical skills and to enable them to reflect on their own problem solving and decision making practice;
One-to-one meetings with lecturers in their consultation hours and dissertation supervisors to discuss and receive feedback on a particular piece of work; and
Potential external visits which constitute field tripts outside the usual learning environments in order to enable students to observe the application of theory in practice.
Assessment methods
Assessment methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Learning Outcomes C1 to C4 will be formally assessed by via coursework assignments and written examinations;
Lecture Outcome C1 will be formally assessed by group presentations;
Learning Outcomes C1 to C4 will also be informally assessed through lectures and seminar activities and discussions, one-to-one discussions with lecturers during consultation hours and feedback received in lab based exercises; and
In addition, the dissertation project (where completed) will assess learning outcome C4.
D: Key skills
D1: Oral and written communication to different audiences in a coherent, cogent and effective manner.
D2: Use of information technologies including word processing, spreadsheets, databases, data analytics and simulation based technologies and tools, statistical analysis software and web-based packages to read, synthesise, analyse and evaluate different types of data and information.
D3: Use and manipulate different types of numerical data, solve mathematically based problems, apply and interpret statistical and visual data.
D4: Use and application of analytical, and other creative problem solving skills.
D5: Understanding and appreciation of different communities of interest, good spoken and written communication skills, empathy and resolution of conflict.
D6: Work as project management, including time management, critical task prioritisation, meeting deadlines, evaluating self- learning.
Learning methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Lab based exercises using a variety of data analytics, simulation based and statistical data analysis techniques and tools will help students to gain the required numeracy and problem solving skills which will be of value in their future work experience;
Formally assessed presentations, and informal presentations, peer group interactions and discussions in lectures and seminars will enable students to orally communicate and present their conclusions to a range of audiences;
Group coursework and presentations will develop students’ skills in operating effectively in a range of team roles and where applicable take on leadership roles;
Individual and group coursework, dissertation project, and written examinations to enhance writing communication skills of students;
Assessment methods
Postgraduate Certificate stage, Postgraduate Diploma stage, and Masters stage:
Learning Outcomes D1, D2, D3 D4 and D6 will be formally assessed by individual assignment projects;
Learning Outcomes D1 to D6 will be formally assessed by group assignment projects;
Learning Outcomes D1, D5 and D6 will be formally assessed by group presentations;
Learning Outcomes D1, D2, D3 and D4 will be informally assessed by lab based exercises;
Learning Outcomes D1, D4 and D5 will be informally assessed by lecture and seminar activities and discussions (e.g. case study discussions);
Learning Outcomes D1 will be assessed by one-to-one discussions with lecturers during consultation hours; and
In addition, the dissertation project (where completed) will assess learning outcomes D1, D2, D3, D4 and D6.