LSI

Module Specification (Flexible Online)

Modern Database Systems



Modern Database Systems

In an era where data drives decision-making and innovation, understanding the underlying architecture of database systems is crucial. This module offers an in-depth exploration into data modelling, database structures, and advanced data management techniques, providing a comprehensive toolkit for future database professionals.

This module will delve into key concepts such as relational and non-relational databases, transaction management, and advanced querying mechanisms. You will learn about contemporary solutions like NewSQL and cloud-based platforms, as well as modern alternatives like GraphQL and in-memory databases. The scope also covers critical aspects like database security, backup and recovery strategies, and emerging technologies.

You'll benefit from practical knowledge that directly applies to real-world scenarios, gaining expertise that enhances your career prospects. With insights into current trends and future-proofing technologies, you will be prepared to tackle complex data challenges and contribute effectively in any data-centric role.

Mode(s) of Study Code CATS Credits ECTSCredits Framework HECoSCode
Flexible online DS71O 30 15 FHEQ - L7

Prerequisites and Co-requisites

None

Learning Outcomes

Code AttributesDeveloped Outcomes
LO1 Knowledge and Understanding Analyse the characteristics and use cases of relational, non-relational, and emerging database technologies.
LO2 Knowledge and Understanding Critically evaluate data modelling techniques, including ERD and normalisation, within modern database systems.
LO3 Intellectual Skills Assess the implications of different transaction management approaches, including ACID properties and eventual consistency.
LO4 Intellectual Skills Formulate advanced strategies for implementing and managing a variety of database structures in real-world scenarios.
LO5 Technical/Practical Skills Design appropriate data models and abstractions for real-world business requirements.
LO6 Professional/Transferable Skills Strategically evaluate the ethical and professional considerations in database management and decision-making processes.

Student Workload

The methods of teaching and learning for this module are based on LSI's Technical 30 teaching system, consisting of the following activities.

Activity TotalHours
Introductory lecture 1.50
Concept learning (knowledge graph) 36.00
AI formative assessment 18.00
Workshop/Lab Sessions 27.00
Independent reading, exploration and practice 153.50
Summative assessment 64.00
Total: 300.00

Teaching and Learning Methods

Activity Description
Introductory lecture

This first weekly session features a specially recorded video by the module leader for online learners, providing a comprehensive introduction to the module. The video outlines the significance of the subject and its interrelation with other modules. No preparation is required from students prior to this session.

The module leader will also provide a structured breakdown of the content to be covered in the subsequent 10 sessions. Students will access a dedicated learning portal, which will include essential reference materials and suggestions for supplementary reading. The format and criteria for the summative assessment will be clearly outlined to ensure understanding of expectations.

The video will also explain how the interactive learning platform utilises generative AI tools to enhance the learning experience, offering tailored resources and adaptive quizzes. A discussion board will promote peer interaction, allowing students to share insights and ask questions, while weekly reflection prompts will encourage critical thinking and deeper engagement with the material.

A dedicated section for submitting queries will ensure timely responses from the module leader. This structured approach promotes a high-quality academic experience, supporting student engagement and learning in an online environment.

Concept learning (knowledge graph)

Our institution's approach to teaching is primarily based on flipped learning. Ahead of each weekly session (Workshop/Lab), students will be required to study the essential concepts that are used in the coming session so they are familiar with the theories and ideas related to that session. The study material will be in the form of written content, illustrations, pre-recorded lectures and tutorials, and other forms of content provided through the AGS.

This content is self-navigated by the students, accommodating different learning styles and schedules, allowing students to watch or listen to them at their own pace and review them as needed.

AI formative assessment

Once each concept of the theory is studied, students will be prompted to engage in formative assessment with instant AI feedback. They include multiple-choice questions, socratic questions and answers, written questions, role-play and other AI-assisted practice scenarios.

The purpose of this automated formative assessment is to provide students with immediate feedback on their understanding of module material and highlight any areas that need support or further study. They are also used to track student progress, boost motivation and promote accountability.

Workshop/Lab Sessions

For those studying in the self-paced online mode, live classes will be replaced by a set of flexible, self-directed activities designed to be completed independently. These include AI-led simulations, interactive videos, reflective prompts, and real-world case studies, all aimed at deepening understanding and fostering critical, independent thinking. AI avatars will simulate a classroom environment, allowing students to interact with virtual instructors for guidance or discussion, creating a more immersive experience. This structure promotes a high-quality, autonomous learning experience, equipping students with skills essential for both academic and professional success. Additionally, a dedicated feature for submitting questions to the module leader will provide timely responses and support.

Independent reading, exploration and practice

This activity challenges students to engage with the reference material and independently explore and analyse academic literature related to the course topic. Students are expected to select relevant sources, practice critical reading skills, and where applicable technical skills, and synthesise information from multiple references. This is an opportunity to enhance research abilities, critical thinking, and self-directed learning skills while broadening and deepening subject knowledge.

Summative assessment

Summative assessments are used to evaluate student learning at the end of a module. These assessments can take many forms, including exams, papers, or presentations. Instructors can use summative assessments to measure whether students have achieved the learning outcomes for the module and provide them with a sense of their overall progress. Summative assessments can also be used to evaluate the effectiveness of the teaching methods used in the module.


Assessment Patterns

Weighting Format Outcomes assessed
40 Invigilated Exam
This is a time-limited examination undertaken during the summative assessment period under the School’s remote invigilation conditions to support quality and academic integrity.

The examination enables students to demonstrate achievement of the module learning outcomes, particularly in relation to knowledge and understanding, and where relevant professional and transferable skills.

Questions may include problems, issues or dilemmas reflecting situations students could encounter in professional practice. Students are expected to synthesise and apply their learning to analyse the issues and reach sound, reasoned judgements.

To support preparation, formative assessment activities, including quizzes, dialogues and an AI-augmented assignment, are built into the module. Students receive actionable feedback from AI, staff and peers to help improve future work and develop their ability to give constructive feedback to others.
I LO3
I LO4
K LO1
K LO2
P LO6
60 Technical Analysis and Solution Assessment Coursework
This coursework assessment requires students to develop a solution to a complex problem in a simulated context, then analyse and reflect on the solution, the decisions they made, and the theory underpinning their approach. It assesses students’ ability to develop practical solutions, critically evaluate their work, and demonstrate their understanding of the module’s technical and theoretical concepts.
I LO3
I LO4
K LO1
K LO2
P LO6
T LO5

References/Indicative Reading List

Importance ISBN Description
Core Textbook 9781119907428 Gillenson, Mark L. Fundamentals of database management systems. John Wiley & Sons, 2023
Core Textbook 9789388176620 Negi, Mukesh. Fundamental of Database Management System: Learn essential concepts of database systems. BPB Publications, 2019
Supplementary Reading Graphical interface for MongoDB. Viewing and querying document structures, exploring schemas and working with MongoDB data visually.
Supplementary Reading 9789381159316 Mittal, Aditya. Introduction to Database Management System. Laxmi Publications, 2017
Supplementary Reading 9781774696736 Kuzmiakova, Adele. The Creation and Management of Database Systems. Arcler Press, 2023
Supplementary Reading Tool for generating diagrams from text-based definitions. Producing ERDs, architecture diagrams and data-flow diagrams using text-based notation.
Supplementary Reading 9780132943260 Connolly, Thomas M., and Carolyn E. Begg. Database systems: a practical approach to design, implementation, and management. Pearson Education, 2015
Supplementary Reading 9780201530902 Elmasri, Ramez. Fundamentals of Database Management Systems. Pearson, 2016
Supplementary Reading Database management and SQL client supporting multiple database systems. Exploring schemas and data, running SQL queries and comparing database structures.
Supplementary Reading 9781783322138 Vidhya, V. Jeyaram, G. Ishwarya, K.R. Database Management Systems. Alpha Science International, 2016
Supplementary Reading In-memory data store for learning and experimentation. Exploring key-value storage, caching, TTL, fast data access and scalability concepts.
Supplementary Reading Cloud-based database platform. Exploring document-oriented NoSQL databases, collections, documents and NoSQL data modelling.
Supplementary Reading Browser-based database modelling tool. Designing relational schemas and visualising tables, primary keys, foreign keys and relationships.
Supplementary Reading Free browser-based diagramming tool. Creating Crow’s-foot ERDs, logical data models, database architecture diagrams and data flows.
Supplementary Reading 9781627343893 Wang, Shouhong and Wang, Hai. Business Database Technology (2nd Edition): Theories and Design Process of Relational Databases, SQL, Introduction to OLAP, Overview of NoSQL Databases. Universal Publishers, 2022
Supplementary Reading 9781779561732 Ahmed, W. Advanced Database Systems. Toronto Academic Press, 2024
Supplementary Reading Relational database management system. Practising SQL, relational design, constraints, transactions, locking and concurrency control.
Supplementary Reading 9781000522457 Chandra, J. Database Management System: An Evolutionary Approach. Chapman and Hall/CRC, 2022
Supplementary Reading Query language and runtime specification for APIs. Exploring GraphQL queries and understanding its role as an API/data-access layer within contemporary data platforms.

Related Programmes

Programme Term Type
1 MSc Digital Project Management 2 Optional
2 MSc Data Science and Analytics 1 Core

Module Review and Approval

Version Date ReviewedBy NextReview
1.0 dd MMMM yyyy Kosmas Kosmopoulos October 2027
Note: The information detailed within this record is accurate at the time of publishing and may be subject to change.

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