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University of Exeter Business School

Topics in Business Analytics

Module titleTopics in Business Analytics
Module codeBEMM457
Academic year2023/4
Module staff

Dr Romanus Okeke (Convenor)

Mr Ahmed ELKattan (Convenor)

Duration: Term123
Duration: Weeks

11 - Sept start

9 - Jan start

Number students taking module (anticipated)


Module description

This module will introduce the key ideas and current topics in business analytics. It will act as a foundation for the programme and will introduce you to key concepts and ideas as well as offer a preview of the modules in term 2. It will highlight the importance of data to organisations and how it can be used to improve firm performance in relation to competitors, customers, employees and processes. The module will introduce you to how data and analytic methods can be used to support an organisation’s overall strategy. The module will also consider ethical, regulatory and security issues associated with data and its use within a business environment.

Module aims - intentions of the module

Business analytics, data science, digital economy, big data – with buzzwords coming and going it can be a complex and confusing picture, and difficult to know where to start.  This module aims to introduce key topics that you’ll need to explore in more depth as you proceed on your ‘business analytics journey’. 

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

  • 1. P2: Demonstrate knowledge and understanding of key business processes and structures, and the role of business analytics in decision support
  • 2. P3: Critically analyse and discuss current issues and influences relevant to the ongoing development of business analytics, and its application
  • 3. P4: Draw on knowledge of current research and practice to identify and apply appropriate analytics methods and tools to a range of business situations

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

  • 4. P7: Critically analyse and interpret relevant academic, technical and industry literature
  • 5. P9: Communicate effectively through oral presentations and written reports, presenting methodologies and findings in a way that is appropriate to the intended audience

ILO: Personal and key skills

On successfully completing the module you will be able to...

  • 6. P12: A collaborative mind-set: Our graduates are enterprising and motivated individuals who are able to actively collaborate and effectively communicate within a range of diverse settings
  • 7. P13: An ethical ethos: Our graduates understand the social, financial and environmental factors that can impact on corporate sustainability and are able to make decisions openly and responsibly
  • 8. P16: A critical thinker: Our graduates have a commercial awareness that enables them to critically analyse, conceptualise and evaluate the challenges facing business

Syllabus plan

The following content will be covered during the course:

  • ‘The fourth industrial revolution’, analytics and data science in business
  • Data ethics, governance and professional responsibility
  • Introduction to Business Analysis
  • Analytics and data science processes and frameworks
  • Introduction to key data science & modelling concepts
  • Introduction to tools commonly used in analytics and data science

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled learning and teaching activity30Scheduled lectures and workshops
Scheduled learning and teaching activity6Scheduled labs and practical sessions
Guided independent study60Background and preparatory reading
Guided independent study54Preparation and delivery of assessments

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
In-class quizzes and exercisesIn class1 - 5Verbal
Group presentationIn class1, 2, 5, 6Verbal

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Group presentation (video)4015 mins1, 2, 5, 6Written
Individual coursework602,750 words1 - 8Written

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Group presentation (40%)Individual presentation (15 minutes, 40%)1, 2, 5Summer reassessment period
Individual coursework (60%)Individual coursework (2,750 words, 60%) 1 - 8Summer reassessment period

Re-assessment notes

Re-assessment will be in nature to the original assessment, but the topic, data, and materials must be new.

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a reassessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.

Indicative learning resources - Basic reading

Guided reading will be provided via module ELE pages in advance of scheduled lectures and workshops. The following resources, available online via the University Library, are indicative of the type and level of information you should expect to review: 

  • Provost, F., & Fawcett, T. (2013). Data science for business: What you need to know about data mining and data-analytic thinking. Sebastopol, Calif.: O'Reilly
  • Kohavi, R., Rothleder, N. J., & Simoudis, E. (2002). Emerging trends in business analytics. Communications of the ACM45(8), 45-48
  • Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research261(2), 626-639

You should also expect to review materials from academic journals such as Management Science (INFORMS) and Journal of Business Analytics (Taylor and Francis), and publications representative of current analytics practice within industry and government.

Key words search

Business, Analytics, Data Science, Ethics, Digital, Industrial Revolution

Credit value15
Module ECTS


Module pre-requisites

This module is closed to MSc Business Analytics students only

Module co-requisites


NQF level (module)


Available as distance learning?


Origin date


Last revision date