Data Intelligence in Practice - BUSN7980

Looking for a different module?

Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2024 to 2025
Spring Term 6 15 (7.5) Ricky Mak checkmark-circle


The aim of this hands-on and highly practical module is to introduce students to the power of data intelligence in transforming the way businesses operate. Students will learn how to develop a successful big data strategy and deliver organisational performance improvements through the use of data analytics. Students will have hands-on exercises primarily based on spreadsheet tools such as Excel and will gain a basic knowledge of coding tools such as Python.
Indicative topics covered in the module include: business intelligence principles, data visualisation and dashboards, data warehouse and integration, artificial intelligence in business applications, big data, social network analysis, text mining, and participatory approaches for problem structuring.
Students will be exposed to a variety of case studies which demonstrate how pervasive data intelligence and analytics have become in every industry and sector, including examples from supply chain management, transport, marketing, finance, healthcare, and human resources. By the end of the module, students will have an understanding of how specific companies use big data and a grasp of the actionable steps and resources required to utilise data effectively.


Contact hours

Private Study: 128
Contact Hours: 22
Total: 150

Method of assessment

Main assessment methods:
In-Course Test 1 (45 minutes) 20%
In-Course Test 2 (45 minutes) 20%
Group Presentation 20%
Individual Report (1500 words) 40%

Reassessment methods:
100% coursework

Indicative reading

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Display conceptual understanding of the usefulness of data in improving business and organisational performance.
- Develop systematic approaches to realising the benefits of data to organisations that align with overarching business strategy;
- Critically analyse the data requirements for improving an area or process of a business.
- Create visualizations and interactive dashboards to gain new insights from data.
- Leverage the power of data-driven storytelling to help messages resonate with a business audience.
- Understand how to employ participatory methods in identifying data requirements, structure complex problems, and ensure stakeholder uptake of data intelligence solutions.

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Identify and critically analyse complex business problems amenable to a data-driven solution.
- Appreciate the power of data intelligence for decision making and business value creation.
- Work effectively individually and in groups.
- Deliver effective oral presentations to engage a business audience and gain buy-in of the usefulness of analytics solutions for complex managerial problems.


  1. Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
Back to top

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.