Foundation degrees

Course Information

Multi-structured Data and NoSQL Technology

Module summary

Module code: COMP1707
Level: 7
Credits: 15
School: Liberal Arts and Sciences
Department: Computing and Information Sys.
Module Coordinator(s): Tatiana Simmonds



With the growing volumes of unstructured and multi-structured data used by modern services and intelligent e-commerce, the relational databases are limiting and inflexible. New-generation NoSQL (Not Only SQL) databases are better suited to deal with vast volumes of diverse data.
This course will discuss the rationale, current trends and features of modern NoSQL approach, including understanding NoSQL concepts and evolution, characteristics and significance of NoSQL databases, their strengths and weaknesses, and how to choose the best one that fit the particular business needs.
The course will examine industry challenges and solution use cases of NoSQL and Big Data approach. It provides students with the tools and techniques to implement and manage complex unstructured data storage systems; it equips students with the skills required to develop creative solutions to information system problems using the latest database technologies.

Learning outcomes

On successful completion of this course a student will be able to:

1. Demonstrate a systemic knowledge and critical awareness of the NoSQL database concepts, technologies and market trends.
2. Design and build data systems employed by various NoSQL databases.
3. Devise strategies for managing different multi-structured data formats and polyglot persistence.
4. Demonstrate skills, self-direction and originality in identifying and solving various modern Big Data problems.

Indicative content

NoSQL concepts and evolution;
Multi-structured data formats;
Polyglot Persistence;
Using Key Value-based Databases;
Managing Document-based Databases;
Processing Data using Column Family-based Databases;
Employing Graph-based Databases; Scalability and Flexibility;
Data manipulation between database systems.

Teaching and learning activity

Lectures - (1 hour) to introduce concepts and necessary theoretical background.
Lab work - (2 hours) to develop practical skills needed to apply the theoretical concepts.


Coursework - 100% weighting, 50% pass mark.
Learning Outcomes - All.
Outline Details - Building a system based on the case study.

Formative Assessment:
Feedback on quiz (logbook) results
Feedback from lab tutors on lab-based tutorial exercises