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University of Exeter Business School

Analytics and Visualisation for Managers and Consultants

Module titleAnalytics and Visualisation for Managers and Consultants
Module codeBEM3064
Academic year2023/4
Module staff

Dr Shirley Atkinson (Lecturer)

Duration: Term123
Duration: Weeks


Number students taking module (anticipated)


Module description

In this module you will develop the skills necessary to communicate analytical results to senior managers. You will learn the consulting skills necessary to understand business problems and develop solutions based upon analytics. The module will develop your skills in communicating information about data visually and verbally. You will learn how to use visualisation tools such as Python libraries and commercial software such as Tableau.

Module aims - intentions of the module

“A good sketch is better than a long speech” - often attributed to Napoleon Bonaparte

This module focuses on the skills necessary to communicate data and results to others.
Students will learn the best practices for creating effective visualisations.
Students will be able to assess the quality of visualisation approaches.
Understand the most appropriate method of visualising a variety of data types.
Present information that facilitates decision making.

Students will learn to deliver an ‘elevator pitch’, critique and improve existing visualisations, and undertake a final project to demonstrate their visualisation skills.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

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

  • 1. demonstrate knowledge and understanding of fundamental, and domain specific, analytics methods and tools;
  • 2. create, manage, interrogate, interpret and visualise data from a wide range of different sources, types and including structured and unstructured forms.

ILO: Discipline-specific skills

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

  • 3. 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...

  • 4. demonstrate 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;
  • 5. demonstrate technological and digital literacy: Our graduates are able to use technologies to source, process and communicate information.

Syllabus plan

“What about confusing clutter? Information overload? Doesn't data have to be "boiled down" and "simplified"? These common questions miss the point, for the quantity of detail is an issue completely separate from the difficulty of reading. Clutter and confusion are failures of design, not attributes of information.” - Edward Tufte

Fundamentals of visualisation. We will review and apply research on effective data visualisation clear up chart junk and design complex, effective visualisations. We will consider cross-cultural concerns and bridging boundaries in expertise.

The Visualisation Toolbox. Students will confront the variety of forms of data and the different strategies designers and researchers have created for translating information into a visual form: time and change, geography and cartography, relationships and networks. 

Communicating Uncertainty. All models are false, but some are useful. Noise and error are part of all analytic models, and communicating relative certainty is critical for making sound decisions.

Designing a Narrative. The module is designed to encourage students to distill data into an engaging story that communicates efficiently. 

Dashboards and User Experience. We will cover animation, and effective dashboard design. Students will learn principles of user experience and how to create interactive dashboards that give control of the data to the managers and executives who are making decisions. 

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 Activity25Class meeting time
Guided Independent Study10Preparatory video lessons and podcasts on topics regarding visualisation and using software
Guided Independent Study25Preparatory reading prior to class meeting time
Guided Independent Study20Preparation for short presentations
Guided Independent Study30Reading and preparation for visualisation critique assignment
Guided Independent Study40Reading and preparation for final visualisation project

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Daily in-class exercisesDuring class hours1-5Verbally

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
Short presentation305-min presentation, 2-3 hours to prepare1-5Written feedback, and in-class feedback
Visualisation critique301,000 word equivalent1, 2, 3Written digital feedback
Final visualisation project403,000 word equivalent1-5Written digital feedback

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Short presentationRecorded 5-min video presentation (30%)1-5August/September Reassessment Period
Visualisation critique1,000 word equivalent (30%)1, 2, 3August/September Reassessment Period
Final visualisation project3,000 word equivalent (40%)1-5August/September Reassessment Period

Indicative learning resources - Basic reading

Indicated texts (not required, but will be referenced in the course).

  • Simon, P. 2014. The Visual Organization: Data visualisation, Big Data, and the Quest for Better Decisions. Hoboken, NJ: Wiley.
  • Sosulski, Kristen. 2018. Data Visulization Made Simple. Routlege. ISBN: 978-1138503915

  • Tufte, E. R. 2001. The Visual Display of Quantitative Information, vol. 2. Graphics press Cheshire, CT.

Indicative learning resources - Web based and electronic resources


  • Students will use Python and Visual Studio Code in class.
  • We will use Tableau at times for dashboards.
  • Inkscape will be used for manipulating images
  • We will be using Javascript using the D3.js library to create interactive, data-driven documents. Minimum requirement is an internet browser and a text editor (notepad, gedit, Sublime Text, Notepad++, etc.)

Key words search

Visualisation, Tableau, Dashboards, Analytics

Credit value15
Module ECTS


Module pre-requisites

BEM1024 OR BEE1022 OR BEE1025 OR BEA1012



NQF level (module)


Available as distance learning?


Origin date


Last revision date