Course coordinator
Dr Rocky Chen
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Database technology is a fundamental part of information technology and plays an important role in data analytics. Database technology is used to store and manage data with reliable services such as data integrity, shareability, recoverability, and security. In this course, we will study data modelling, representation, query and maintenance of data integrity. Hands-on experiences will be provided for students to create a basic database application system. In order to provide effective and efficient data management, we will study algorithms for effective access to structured data with different data processing requirements.
This course entails three main modules:ﾠ
[1. Relational Database] This module packs necessary concepts to correctly design, and implementﾠan ﾠinformation system.ﾠ
[2. Data Structure] This module covers ﾠthe fundamental data structures and data access algorithms, which are the mathematical backbone for data ﾠindexing and optimisation in relational databases.
[3. Indexing and Query Processing] This module provides an overview of the logical foundation of how data is indexed and how a database query is executed and optimised.
Course requirements
Assumed background
No computer programming experience is assumed for this course. Knowledge of the set theory will be useful.
Incompatible
You can't enrol in this course if you've already completed the following:
INFS1200, INFS2200, INFS7900 and INFS7903
Course contact
Course staff
Lecturer
Dr Rocky Chen
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The course aims to introduce students to principles of databases. In the first module, concepts necessary to correctly designﾠand implementﾠa small information system using relational databases are presented. In the second module, ﾠbasic fundamental data structures and algorithms, which form the basis of indexing and optimisation in relational database management systems are covered. Finally, in the third module, methods of indexing and query optimisation in relational models are introduced.
ﾠ
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Reason with the logical foundation of the relational data model and understand the fundamental principles of correct relational database design.
LO2.
Express natural language queries using relational algebra and SQL.
LO3.
Analyse the fundamental techniques and algorithms applied for sorting, tree manipulation, and hashing on structured data.
LO4.
Reason with the logical foundation on how data is indexed and how a query is executed and optimised.
LO5.
Design relational databases with considerations of data integrity and system performance.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Project | Part 1 - Database Design Proposal | 20% |
4/04/2025 3:00 pm |
| Project | Part 2 - Database SQL Implementation | 20% |
23/05/2025 3:00 pm |
| Tutorial/ Problem Set |
Collaborative Learning Exercises
|
10% |
30/05/2025 3:00 pm |
| Examination |
Final Exam
|
50% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Part 1 - Database Design Proposal
- Mode
- Written
- Category
- Project
- Weight
- 20%
- Due date
4/04/2025 3:00 pm
- Learning outcomes
- L01, L05
Task description
In this project, each student is required to select an application that would benefit from a database, and build a database application from start to finish with the skills learned from this course. This assessment item corresponds to the first part of the project:
(1) The first part of this project is the proposal outlining the project scope, ER diagram, schema, and associated information
Note: This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Part 2 - Database SQL Implementation
- Mode
- Written
- Category
- Project
- Weight
- 20%
- Due date
23/05/2025 3:00 pm
- Learning outcomes
- L02, L05
Task description
In this project, each student is required to select an application that would benefit from a database, and build a database application from start to finish with the skills learned from this course. This assessment item corresponds to the second part of the project:
(2) The second part of this project is the code implementation and final report based on the database designed.
Note: This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Collaborative Learning Exercises
- Online
- Mode
- Activity/ Performance
- Category
- Tutorial/ Problem Set
- Weight
- 10%
- Due date
30/05/2025 3:00 pm
- Other conditions
- Peer assessment factor.
- Learning outcomes
- L01, L02, L03, L04
Task description
You are required to author learning resources and engage with resources from your peers. You are required to complete the tasks for two problem sets that respectively focus on:
(1) ER Diagram, Relational Model, Functional Dependencies, Normalization, and SQL Programming;
(2) Asymptotic Analysis, Sorting, Binary Trees, Hashing, Indexing, Relational Algebra, and Query Optimization.
The full description of the platform used and the assessment is available on the course website.
Note: This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission will be managed through RiPPLE, UQ's own interactive learning platform. Corresponding instructions and guidelines will be made available on Blackboard.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 3 days. If there are exceptional circumstances, an exemption may be approved and may involve submitting/discussing your work as it stands. Exemptions must be requested as an extension with a note specifying exemption via my.UQ.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
100% Late Penalty after one hour grace period. The one-hour grace period is recorded from the time the submission is due.
Final Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
Exams are designed to test theoretical concepts and modelling techniques introduced in lectures and tutorials.
Delivery Mode: On-campus invigilated exam.
Timing: The final exam will be hosted during Semester 1's exam period.
Permitted Materials: This exam allows one piece of A4 paper with notes (printed or handwritten) on both sides.
Hurdle requirements
This is a double-pass course. Students must score a minimum of 50% in the final exam. If you fail the final exam, your total mark will be capped at 49 and your final grade will be capped at 3.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | Any calculator permitted |
| Open/closed book | Closed Book examination - specified written materials permitted |
| Materials | One A4 sheet of handwritten or typed notes, double sided, is permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Marks | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 20 - 46 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
Grades: Results of all assessment items will be combined as per the weightings above to calculate the total mark. The total mark will be rounded to the nearest integer number before being converted to the 7-point grade format.ﾠ For example, a total mark of 84.5 is rounded to 85, and then converted to a grade of 7.
Hurdle: This is a double-pass course. Students must score a minimum of 50% in the final exam. If you fail the final exam, your total mark will be capped at 49 and your final grade will be capped at 3.
Supplementary assessment
Supplementary assessment is available for this course.
If you received a grade of 3, or a non-graded ‘N’, then you may be eligible for a supplementary assessment. The supplementary assessment lets you re-take the final exam which has a different exam sheet. After the supplementary assessment, the highest grade you can receive is a 4.
Additional assessment information
Having Troubles?
If you are having difficulties with any aspect of the course material, you should seek help and speak to the course teaching staff.
If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help; for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things).
Complaints and criticisms should be directed in the first instance to the course coordinator. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lectures The course lectures will provide in-depth knowledge of various concepts and techniques in the design of Database Management Systems (DBMS). Lecture notes will be available for all the material covered in this course. A series of in-class questions related to the course content will be raised to provide opportunities for better student engagement with content and in-depth discussions. Learning outcomes: L01, L02, L03, L04, L05 |
Multiple weeks From Week 2 To Week 12 |
Tutorial |
Hands-on Tutorials Hand-on Tutorials will provide an opportunity to further practice the concepts introduced in the lectures via examples, exercises and problem-solving. They will also allow students to become familiar with various methods in the implementation and optimization of database systems. Learning outcomes: L01, L02, L03, L04, L05 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: