Gwybodaeth Modiwlau

Module Identifier
CSM6020
Module Title
Big Data
Academic Year
2021/2022
Co-ordinator
Semester
Distance Learning
Pre-Requisite
Other Staff

Course Delivery

 

Assessment

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

Assessment Type Assessment length / details Proportion
Semester Assessment Project and report  (Project based assignment plus 5,000 word report)  100%
Supplementary Assessment Project and report  (Project based assignment plus 5,000 word report)  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.

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.

Content

Introduction to NoSQL.

1. Using a NoSQL data management system.

2. Querying an existing NoSQL database

3. 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.

4. Creating a NoSQL data model, implementing the model and querying the resulting NoSQL database.

Data analytics and data mining.

1. Application programming for data analysis

2. Cloud based data management.

3. Exploring alternative NoSQL data models.

4. Vulnerabilities, procedural and technical factors, threat analysis and mitigation.

5. Choosing the 'right' data management system. Evaluating alternative data management systems in terms of data volume, transaction rate and requirements for security and privacy.

Aims

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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

Notes

This module is at CQFW Level 7