Gwybodaeth Modiwlau

Module Identifier
Module Title
Applied Data Mining
Academic Year
Semester 2
Available to MSc students only, a knowledge of Python programming is assumed
Other Staff

Course Delivery



Due to Covid-19 students should refer to the module Blackboard pages for assessment details

Assessment Type Assessment length / details Proportion
Semester Exam 2 Hours   Written examination  50%
Semester Assessment 4,000 word report on practical data management and security issues  50%
Supplementary Exam 2 Hours   Resubmission of failed/nonsubmitted components or others of equivalent value.  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Design and implement a NoSQL database with one or more front-end applications.

2. Evaluate the applicability of different technical data management strategies for a variety of applications.

3. Explain the essential concepts behind a variety of NoSQL data models, including key-value, document oriented and graph data models.

4. Identify potential security issues raised by the use of NoSQL data management systems to handle massive data volumes with high transaction rates, and suggest mitigating strategies.


This module gives students practical in information security (MSc Security) and in data mining (MSc Data Science) using modern data management systems.

Brief description

Querying, searching, mining and analyzing very large amounts of data demands procedural and technological approaches that go beyond those typical of relational database systems.


1. Introducing NoSQL. Using a NoSQL data management system (2 hours seminar)
Querying an existing NoSQL database (2 hours practical)

2. Modelling, securing and processing massive volumes of data with high transaction rates. Case studies in evolution of the NoSQL movement and alternative approaches to data management. (3 X 2 hours seminars)
Creating a NoSQL data model, implementing the model and querying the resulting NoSQL database. (2x2 hours practical}

3. Data analytics and data mining.
Introducing the practical assignment. (2 hours seminar)
Application programming for data analysis. (2x2 hours practical)

4. Cloud based data management. (2 hours seminar)
Exploring alternative NoSQL data models (2x2 hours practical )

5. Vulnerabilities, procedural and technical factors, threat analysis and mitigation. (3x2 hours seminar, 3x2 hours practical )

6. Choosing the 'right' data management system. Evaluating alternative data management systems in terms of data volume, transaction rate and requirements for security and privacy. (2 hours seminar)

Module Skills

Skills Type Skills details
Application of Number Inherent to subject
Communication Through assignment
Improving own Learning and Performance Inherent to subject
Information Technology Technical skills related to applying emerging data management systems to problems involving massive volumes of data and high transaction rates.
Personal Development and Career planning Encourages students to see roles in subject for career and personal development
Problem solving Inherent to subject
Research skills Inherent to subject
Subject Specific Skills Technical skills related to applying emerging data management systems to problems involving massive volumes of data and high transaction rates.
Team work No


This module is at CQFW Level 7