CSC-20065 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

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.

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 and explore evaluation and application of the most appropriate visualisations for a given situation, explaining the benefits and limitations.

Intended Learning Outcomes

compare contemporary uses and theoretical concepts from the academic literature in big data and their impact on areas such as business intelligence: 1
produce appropriate visualisations for a given authentic case study to enable analysis and decision making in either a business or academic research context: 1
apply data analytics in an authentic real world case study and report the analysis and conclusions for either a business or academic audience: 1

Study hours

20 hours (approx) supported online practical activities conducted with some sessions available during block release.
10 hours of online lectures with associated guided reading.
Assignment 40 hours.
Independent Learning 80 hours.

School Rules

None

Description of Module Assessment