MARK1256 Data Analytics for International Business Decisions Module Handbook | UoG

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Published: 30 Sep, 2026

Category	Assignment	Subject	Business
University	University of Greenwich	Module Title	MARK1256 Data Analytics for International Business Decisions

Module details and learning outcomes

Host faculty: Business
Host school: Management and Marketing
Number of credits: 15
Term(s) of delivery: Term 2
Site(s) of delivery: Greenwich
Pre-requisite modules: None
Co-requisite modules: None

Aims:

This module aims to provide students with a practical grounding in the skills and techniques necessary to make sound business and marketing decisions through data analysis.

Learning Outcomes:

On successful completion of this course a student will be able to:

1. Critically appraise and make decisions based on multi-source marketing and business information.

2. Critically evaluate the role of marketing analytics in simulating and predicting consumer behaviours, drawing on industry practice and real-life data.

3. Critically evaluate the role and value of consumer data and big data analytics, with a focus on its ethical responsibilities, in supporting international marketing decision making, using a variety of topical examples.

Glossary:

A pre-requisite module is one that must have been completed successfully before taking this module.
A co-requisite module is one that must be taken alongside this module.
A learning outcome is a subject-specific statement that defines the learning to be achieved through completing this module.

Employability

a. Cognitive Skills

You will be exposed to problems facing businesses in the digital space. This gives you the opportunity of working on your evaluation and problem-solving skills as well as encouraging reasoned judgement.

b. Generic Awareness

You will be working and managing teamwork throughout this module. This should develop your teamwork and leadership skills by not only working together but also by exploring team dynamics, and team member roles and differences. In addition, there are opportunities for reflection throughout the term. Such skills are attractive to potential employers and should enable you to be the next graduates with great impact.

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Schedule of teaching and learning activities

(Subject to change)

Week number.	Week beginning.	Activity.
19.	13ᵗʰ Jan 2025	Introduction to the Module<br>Tutorial: Introduction
20.	20ᵗʰ Jan 2025	Managing Data<br>Tutorial: Assessment Briefing
21.	27ᵗʰ Jan 2025	Basic Marketing Analytics - Part 1<br>Tutorial: Assessment Data & Groups
22.	03ʳᵈ Feb 2025	Data visualisation and Storytelling<br>Activity: Excel (Data Preparation)
23.	10ᵗʰ Feb 2025	Basic Marketing Analytics - Part 2<br>Lab/Workshop - Tableau
24.	17ᵗʰ Feb 2025	Dashboard Design and Present Part 1<br>Lab/Workshop - Tableau
25.	24ᵗʰ Feb 2025	Dashboard Design and Present Part 2<br>Lab/Workshop - Tableau
26.	03ʳᵈ Mar 2025	International Week – No Lecture or Tutorials
27.	10ᵗʰ Mar 2025	AI in Marketing Analytics<br>Tutorial: Dashboard Presentation
28.	17ᵗʰ Mar 2025	Assessment - Individual Report<br>Assignment Support (Individual)

The weighting refers to the proportion of the overall module result that each assessment task accounts for.

Your assessment brief:

Al Guidance: GenAl tools can be used to benefit the assessment according to the University's Al Guidance and policy.

Formative assessments:

Students work in groups to collate and analyse datasets pulled from various marketing channels; identify the key information & design a dashboard (visualisations) using Tableau Business Intelligence software.
A data dashboard is a collection of visualisations, a story telling tool businesses use to help track, analyse, and display data, usually to gain deeper insight into the overall wellbeing of the organisation, a department, or even a specific process.
Form groups with 5-6 members
Use the datasets provided on Moodle (CRM, Facebook and Twitter). Identify your business and marketing objectives
Identify the key metrics for business benefits
Create a dashboard in Tableau. (Business intelligence software)
You will receive written feedback within 15 working days. The formative activity allows students to understand the linkage between business environment,
business problem/ opportunities and customers and provide solution with content marketing plan.
Students should form their groups as quickly as possible after the first lecture, more information will be available on Moodle after the first lecture. Names to be
entered in the 'Assessment Teams' link available on Moodle.
No team changes shall be allowed later (the above spreadsheet will be locked for editing after the set date published on Moodle).
It is highly recommended that individuals to keep a log of what they did for the dashboard and how the dashboard is evolved.
More details about the file formats and submission will be available on Moodle.

Summative Assessment:

Individual report - 3000 words (excluding references and appendix, the overall pass mark for this module is 50%). Submit the report online via Moodle.
Work individually to provide a reflective report based on the data dashboard you have created as a group (formative assessment), which covers:

1) a reflection of the dashboard design.

2) the insights from the dashboard.

3) the action plan.

You should cover the following sections in your report:

Reflection on the team effort (dashboard design procedure and how it evolves) Introduction & background of the data and dashboard (datasets used)

1. Executive summary

2.Reflection of the team efforts ( dashboard design procedure and how it evolves

3. Key finding of the dashboard (What did you find based on your analysis

4. Key findings of the dashboard (what did you find based on your analysis)

5.Limitations of the dashboard (discuss the challenges, limitations)

6. Recommendations (what action can you suggest to your executive team)

7. Appendix (screenshots of the dashboard)For more details, please refer "MARK1256 Coursework Instructions" on Moodle site.

Feedback for summative coursework:

The marks and written feedback will normally be provided to students within fifteen working days of the submission deadline. In exceptional circumstances, where there is a delay in providing feedback, you will be informed by the module leader.

Marking rubric:

80-100
Exceptional

70-79
Excellent

60-69

Very Good

50-59

Good

40-49

Satisfactory

0-39

Fail

D1. Knowledge 10%	Articulate an awareness of marketing data analytics; produce a sound executive summary. Ability to relate theory to professional practice. Use of clear, accurate English, well organised, with flow and progression.
D2 Reflective and Critical Evaluation of Group Work 30%	Demonstrates self-direction and originality in tackling and solving problems, and act autonomously in planning and implementing tasks at a professional or equivalent level. Ability to work effectively within a team and contribute own strength in data analysis projects. Demonstrate initiative and personal responsibility in decision-making in complex and unstructured situations.
D3 Research 10%	Sophisticated and comprehensive knowledge of the subject area. An ability to identify relevant information and data related to the context, analyses of the information with a fully justified interpretation of data. Evidence of reading widely on relevant analytics skills and techniques for an informed and critical discussion.
D4 Communication 20%	Develop well-justified marketing report with data evidence and communicate their conclusions clearly to specialist and non-specialist audiences; where appropriate. Critically evaluate relevant information, data and academic reading and apply to the context effectively. Ability in the appropriate use of Tableau to analyse and synthesise data reports at master’s level.
D5 Employability 20%	Draw upon critical evaluation of current knowledge in the field to data analysis. Be able to provide actionable plans based on the Tableau dashboard findings. Be able to identify the limitation of the project, including the dashboard itself, team building, data availability, possible insights to analyse further. Demonstrate a comprehensive and practical understanding of data analysis techniques.
D6 Referencing 10%	Sources used are all acknowledged in the text and reference list/bibliography using correct academic citation - including online sources. Referencing is consistent throughout. Follows a professional approach. Bibliography is outstanding in its breadth and depth. Comprehensive range of evidence used.

Coursework is marked on the understanding that it is the student's own work on the module and that it has not, in whole or part, been presented elsewhere for assessment. Where material has been used from other sources, this must be properly acknowledged in accordance with the University's regulations regarding Assessment Misconduct.

Marking, feedback and next steps

To pass this module, you must achieve an overall mark of 50+ for your assessment.

For coursework, the marks and feedback will normally be provided to students within fifteen working days of the submission deadline. In exceptional circumstances, where there is a delay in providing feedback, you will be informed by the module leader.

If you do not pass a module at the first attempt, you will likely be eligible for a resit opportunity on the failed assessments. The Progression and Award Board (PAB) will decide whether you will be offered an opportunity to resit. Note that marks on resit assessments are capped at 50% unless extenuation has been applied for and granted.

External Examiner

The External Examiner for this module is:

Name: Anni Chen
Institution:

Please note that the role of the External Examiner is to evaluate the overall standard of assessments on the module. They are unable to correspond with individual students about their work. If you need to discuss your marks or feedback, please contact the module leader.

Resist Assessments

Assessments Schedule

First sit Assessments	Deadline or exam period	Weighting out of 100%*	Maximum length	Marking type	Learning outcomes mapped to this assessments
Formative - Build A Data Dashboard Using Tableau (Groupwork)	TBC	N/A		Pass/Fail	1-3
Coursework - Individual Report	TBC	100%	3000 Words (+/-10%)	Stepped	1-3

Please read the examiners feedback, and the resit section of the Moodle page first, and contact the module leader or tutor if you need extra support for re-sits.

Resource recommendations

The following are suggested readings for the module. Additional, more detailed reading recommendations will be provided for the module topics.

Author	Title	Publisher	ISBN
Mike Grigsby<br>(2022)	A Practical Guide to Improving Consumer Insights Using Data Techniques	Kogan	9781398608191
Knaflic, C. N<br>(2015)	Storytelling with Data: A Data Visualization Guide for Business Professionals	John Wiley & Sons	978-1119002253
Loth, A (2019)	Visual Analytics with Tableau	John Wiley & Sons	978-1119560203
Knaflic, C. N<br>(2015)	Storytelling with Data: A Data Visualization Guide for Business Professionals	John Wiley & Sons	978-1119002253
Cairo, A (2016)	The Truthful Art: Data, Charts, and Maps for Communication

Changes to the module

At the University of Greenwich, we value feedback from students as well as External Examiners and other stakeholders and we use this information to help us improve our provision.

Important note: The University of Greenwich will do all that it reasonably can to deliver the module and support your learning as specified in our handbooks and other information provided. However, under some circumstances, changes may have to be made. This may include modifications to the: |

content and syllabus of modules, including in relation to placements
timetable, location and number of classes
content or method of delivery of your module
timing and method of assessments.

This might be because of, for example:

academic changes within subject areas
the unanticipated departure or absence of members of university staff
where the numbers expected on a module are so low that it is not possible to deliver an appropriate quality of education for students enrolled on it industrial action by university staff or third parties
the acts of any government or local authority
acts of terrorism.

In these circumstances, the university will take all reasonable steps to minimise disruption by making reasonable modifications. However, to the full extent that it is possible under the general law, the university excludes liability for any loss and/or damage suffered by any applicant or student due to these circumstances.

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MARK1256 Data Analytics for International Business Decisions Module Handbook | UoG

Module details and learning outcomes

Aims: