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Business Analytics and Research Skills

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.

Full module specification

Module title:Business Analytics and Research Skills
Module code:BEMM389
Module level:M
Academic year:2023/4
Module lecturers:
  • Professor Tim Coles - Convenor
  • Professor Tim Coles - Convenor
Module credit:15
ECTS value:






Duration of module: Duration (weeks) - term 2:


Module aims

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 vizualisation and infographics and their roles in communicating business analytics.

ILO: Module-specific skills

  • 1. Demonstrate understanding of the principles behind, and relative mertis, 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

  • 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

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

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 Activity3Module introduction and basic content (in-class and online)
Scheduled Learning and Teaching Activity11Whole cohort teaching events ('lectures')
Scheduled Learning and Teaching Activity5Scheduled Learning and Teaching activities 5 Small group (thematic) workshops
Guided Independent Study48Preparation 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 Study46Assignment 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
Group assessment30Up to 1000 words (per member)1,2,3,7Electronic, written comments
Individual Report70Up to 2000 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
Group assessment (30%)Individual report (30%)1-6, 8August/September Reassessment Period
Individual Report (70%)Individual Report (2000 words, 70%)1-8August/September Reassessment Period

Syllabus plan

  • 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)

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.

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Indicative learning resources - Web based and electronic resources

  • Kleinberg, S. (Ed.). (2019). Time and Causality Across the Sciences. Cambridge University Press. (Available as E-book through Encore)

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