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COMP20070

Academic Year 2025/2026

Databases and Information Systems I (COMP20070)

Subject:
Computer Science
College:
Science
School:
Computer Science
Level:
2 (Intermediate)
Credits:
5
Module Coordinator:
Dr Anh Vu Vo
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Collection, organisation and storage of data are major tasks in many human activities and in every modern computing system. Computer-based information systems ensure that this data is permanently maintained, quickly updated and made accessible to users. Databases are essential components of computerised information systems. This is a module for all students interested in understanding how to design, develop and query databases. In this module students will learn the fundamentals of database models, database designing methodologies, database querying. They will learn details about the relational database model, relational database query languages (relational algebra/calculus, SQL), the entity-relationship model for database design. From a more practical point of view they will gain experience in building a relational database using a commercial database management system. Students will find these skills very useful in the development of any application requiring the storage and manipulation of data.

About this Module

Learning Outcomes:

On completion of this module students should be able to:
- formulate, explain and compare the fundamental database concepts
- design a relational database (conceptual and logical design using E-R and relational models)
- analyse a relational database table
- express queries in relational algebra and SQL
- implement and query a relational database

Indicative Module Content:

Relational database model, relational database query languages (relational algebra and calculus, SQL), the entity-relationship model for database design.

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Practical

12
Specified Learning Activities

20
Autonomous Student Learning

60
Total

116

Approaches to Teaching and Learning:
- active/task-based learning (examples exercises; problem solving)
- peer/group work where appropriate
- individual work (assignment)

If students are permitted to use generative AI tools in assignments, that will be indicated in the assignment specification.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): In class mid-term test Week 6, Week 7, Week 8 Graded No
20
 Yes
Exam (In-person): Final in-class test Week 11, Week 12, Week 14 Graded No
40
 No
Individual Project: Individual assignment Week 9, Week 10, Week 11, Week 12 Graded No
40
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Self-assessment activities

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Professor Michela Bertolotto Lecturer / Co-Lecturer
Laura Dunne Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 3 Week(s) - Autumn: All Weeks Thurs 12:00 - 12:50
Autumn Lecture Offering 3 Week(s) - Autumn: All Weeks Tues 11:00 - 11:50
Autumn Practical Offering 1 Week(s) - Autumn: Weeks 2-12 Tues 15:00 - 16:50
Autumn Practical Offering 2 Week(s) - Autumn: Weeks 2-12 Tues 15:00 - 16:50
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