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CSC-40048 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

For academic year: 2024/25 Last Updated: 25 April 2024

CSC-40048 - Visualisation for Data Analytics
Coordinator: Steve Linkman Room: CR023 Tel: +44 1782 7 33413
Lecture Time: See Timetable...
Level: Level 7
Credits: 15
Study Hours: 150
School Office: 01782 733075

Programme/Approved Electives for 2024/25

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

The information age is characterised by large amounts of data generated as part of an ever-widening range of day-to-day activities. When properly analysed this data can lead an organisation to better decision-making, insight, and competitive advantage.
The module aims to equip learners with an appropriate understanding of the use of Data Analytics within areas such as health, security, science and business. The module also aims to equip learners with a variety of Data Visualisation techniques to make sense of the emergence and growth of big data.

Aims
This module aims to explore how organisations can use data analytics and how this relates to the information needs of different stakeholders.
It will also cover different data visualisation techniques.
Furthermore, the module will explore evaluation and application of the most appropriate visualisations for a given situation, explaining the benefits and limitations of these techniques.

Intended Learning Outcomes

appraise contemporary uses and theoretical concepts from the academic literature in big data and their impact on areas such as business intelligence: 1
evaluate theoretical and practical visualisation approaches and assess which are the most appropriate for a given real-world case study: 1
design and develop appropriate visualisations for a given real-world case study to enable analysis and decision making in either a business or academic research context: 2
evaluate and interpret how data analytics can be applied to a range of case studies in big data and report the analysis and conclusions in an academic format: 2

Study hours

Lectures 22 hours.
Practical 22 hours.
Assignment 40 hours.
Independent Learning 66 hours

School Rules

Knowledge of Programming is essential. Students not having a background in Programming are required to attend the course CSC-40044 (System Design and Programming) offered by the department.

Description of Module Assessment

1: Report weighted 40%
Report on the use of Data Analytics in Business and Research
Students will work in groups and will produce an academic report on the theoretical concepts and contemporary applications of big data in business and/or research. The report will require an evaluation of why a particular approach was taken, how it was carried out and what were the outcomes. The the report should be a maximum of 4,000 words.

2: Project weighted 60%
Design and Develop a set of visualisations for a given business/research case study
Students will give in a group. Students are provided with a set of raw data and must then evaluate appropriate visualization techniques which they then use to design and develop a set of visualizations which enable conclusions to be drawn by a manager/researcher. Students will produce a report containing justifications for the approach that they have taken; a set of visualisations and related code and development documentation. The project should be the equivalent of 6,000 words.

Please note that for the 2022/23 Academic Year programmes may be adapted to operate in accordance with a flexible, digital approach. This means that there may be some changes made to how modules are delivered and assessed. The latest information will be provided to you by your School in module handbooks. We endeavour to give you as much notice as possible of any changes and details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/student-terms-and-conditions/

Last Updated: 25 April 2024