MKT42370 Advanced Analytics & Big Data

Academic Year 2023/2024

Marketers are increasingly expected to utilise (big) data and analytics to drive decisions in areas such as promotion targeting, campaign optimization or pricing. Marketers are not only faced with an exponentially growing volume of data, but also with a whole new array of technologies, tools and industry players that allow them to translate raw data into actionable insights. This module aims to explore the role of big data, information systems and analytics in marketing management contexts. The module will cover the different sources and types of marketing and customer data; necessary information systems and infrastructure (e.g. CRM systems); the analytical tools and methodologies; the managerial challenges of effectively utilising big data and analytics; as well as the ethics and regulations of marketing and customer data.

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Curricular information is subject to change

Learning Outcomes:

Learning Objectives
• Learn about the sources, types and quality of big data
• Understand the necessary infrastructural investments to harness and cleans big data
• Comprehend core analytical techniques and tools to generate insight from data
• Learn about new industry players and dash-board solutions
• Learn how to effectively summarise, visualise and communicate insights generated from big data.
• Understand the ethical and regulatory dimensions of customer data

Student Effort Type Hours




Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Essay: 1,000 word essay based on 1 of 3 questions Coursework (End of Trimester) n/a Standard conversion grade scale 40% Yes


Group Project: Group work on 1 of 3 case studies (each group can choose one) to bring the data science process to life. Throughout the Trimester n/a Standard conversion grade scale 40% Yes


Carry forward of passed components
Not yet recorded

Not yet recorded

Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Individual component (1,000 word essay): 60% Group component (in-class group research and presentation): 40%

Name Role
Dr Daniel Knapp Lecturer / Co-Lecturer

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