Advanced Data Analytics

Module Identifier
CSM6720
Module Title
Advanced Data Analytics
Academic Year
2027/2028
Semester
Semester 2
Co-ordinator
Dr Otar Akanyeti
Reading List
View on Aspire
Pre-Requisite

Available to MSc students only
Other Staff
Dr David Jones
Dr Otar Akanyeti

Assessment

Assessment Type

Assessment details

Proportion
Semester Assessment Practical assignment and report: with accompanying source code and data. 4000 Words 50%
Semester Exam Written examination: 2 Hours 50%
Supplementary Assessment Practical assignment and report: with accompanying source code and data. 4000 Words 50%
Supplementary Exam Written examination: 2 Hours Students must resit failed examination and/or resubmission of failed/non-submitted assignment work. 50%

Learning Outcomes

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

  1. Design and implement a NoSQL database with one or more data models
  2. Design, perform, visualise and report exploration and analysis of data-set.
  3. Identify and evaluate the essential concepts behind a variety of NoSQL data models, including key-value, document oriented and graph data models.
  4. Identify potential security, ethics and data management issues raised by the use of computerised data storage and processing and suggest mitigating strategies.

Brief description

In order to model the wide variety of phenomena that modern data analysts are expected to cover it is important to be able to understand a wide variety of different data storage methods and data models. This module will cover the essential concepts behind modern database models known as NoSQL. We will cover the process of data analytics from initial data modelling through storage, clearing, retrieval, processing, visualising and analysis of a variety of different data models. In addition we will cover technical, legal and ethical issues associated with data collection and storage.

Aims

This module teaches core data preparation, exploration and analysis for machine learning and data analysis.
This module teaches practical data handling, preparation and storage techniques.
This module covers technical, legal and ethical issues associated with data collection and storage.

Content

1. NoSQL. Using a NoSQL data management system. Querying an existing NoSQL database. Exploring alternative NoSQL data models.

2. Modelling, securing and processing of data. Designing a NoSQL data model, implementing the model and querying the resulting NoSQL database.

3. Data analytics, visualisation and data mining.

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 domain, model and project requirements.

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.

Notes

This module is at CQFW Level 7