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University of Exeter Business School

Business Analytics and Research Skills

Module titleBusiness Analytics and Research Skills
Module codeBEMM389
Academic year2023/4
Module staff

Professor Tim Coles (Convenor)

Professor Tim Coles (Convenor)

Duration: Term123
Duration: Weeks




Number students taking module (anticipated)


Module description

Data is the cornerstone of many businesses.  The ability to make good business decisions relies on the availability, precision and application of data in a number of forms.  For many enterprises, data and analysis is the business as they sell solutions, insights and intelligence to their clients and customers.  This module builds your knowledge and understanding of business analytics; the main principles, ideas and approaches relating to the term; and the major issues associated with using analytics in practice.  Although the module will increase your confidence with data, mainly quantitative in nature, the module makes no assumptions of your prior knowledge of, or training in, research methods.

Module aims - intentions of the module

The aim of this module is to develop your knowledge and skills in business analytics and the broader research skills that underpin them.  Specifically, we will cover:

  • The different types, roles and contexts of business analytics
  • The main principles and practices behind different types of quantitative analytics
  • Research design as the foundation for analytics and decision-making
  • Data visualisation and infographics and their roles in communicating business analytics

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

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

  • 1. Demonstrate understanding of the principles behind, and relative merits, of a range of analytical tools to source, process and evaluate business-related information
  • 2. Explain recent trends in, and drivers for, the use and popularity of business analytics in organisational management and decision-making
  • 3. Deploy in the correct context, different types of analytics and particular techniques to derive insights and inform business decision-making
  • 4. Communicate analytics data and their meaning through visualisations and infographics to appropriate business audiences and stakeholders

ILO: Discipline-specific skills

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

  • 5. Apply spreadsheet software to derive insights from analytics to address defined business challenges
  • 6. Employ presentation software for visually reporting, and communicating the meaning of, findings from analytics on defined business issues

ILO: Personal and key skills

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

  • 7. Conceptualise critical issues in business through alternative analytical prisms
  • 8. Demonstrate enhanced technological and digital literacy

Syllabus plan

Whilst the precise content may vary from year to year, it is envisaged that the syllabus will cover all or some of the following topics:

• Business analytics, business intelligence and decision-making: recent trends and future challenges
• Foundations of business analytics: research design, data processing and quality assurance
• Descriptive, diagnostic and predictive analytics
• Moving beyond the model: meaning and interpretation of analytics
• Communicating business analytics: data visualisation and infographics
• The potentials and pitfalls of particular analytics tools (e.g., Excel / SPSS / R / Python)

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 activities3Module introduction and basic content (in-class and online)
Scheduled learning and teaching activities10Whole cohort teaching events ('lectures')
Scheduled learning and teaching activities10 Group workshops
Guided independent study50Preparation and consolidation (reading) prior to and after lectures and workshops
Guided independent study37Practice use of software and concepts from additional exercises and examples, and from curated online learning resources
Guided independent study40Assignment preparation

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Individual quiz on key ideasMax. 20 questions. 20 mins, available before reading week1-4Numeric (score). 50% indicative pass mark
Outline plan for assessed reportOne page3,5-8Electronic/Verbal

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
Multiple choice questions3090 minutes, 20 questions1,2,3,7Electronic, written comments
Individual report 702000 words 3,4,5,6,8Electronic, written comments

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Multiple choice questions (30%)Multiple choice questions1,2,3,7Referral/Deferral period
Individual report (70%)Individual report (2000 words)3,4,5,6,8Referral/Deferral period

Re-assessment notes

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 re-assessment 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 submit a further assessment as necessary. If you are successful on referral, your overall module mark will be capped at 50%.

Indicative learning resources - Basic reading

  • Albright, S. C., & Winston, W. L. (2020). Business analytics: Data analysis & decision making. Cengage, 7th Edition
  • Ledolter, J. (2013). Data mining and business analytics with R. Hoboken, NJ: Wiley
  • Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley & Sons

Indicative learning resources - Web based and electronic resources


Indicative learning resources - Other resources


Key words search

Business, Analytics, Management, Decision-Making, Research, Methods, Quantitative, Secondary, Data

Credit value15
Module ECTS


Module pre-requisites


Module co-requisites


NQF level (module)


Available as distance learning?


Origin date


Last revision date