Course coordinator
Dr Reihaneh Bidar
Course overview
- Study period
- Semester 2, 2026 (27/07/2026 - 21/11/2026)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
This course examines data analysis, design, and business issues in relation to database management, conceptual and data modelling, and business applications. Students will gain an overall understanding of the relational database model and learn to design and retrieve information from relational databases using Structured Query Language (SQL).
Data plays an integral role in decision-making within modern organisations. Therefore, data needs to be managed efficiently and effectively to enable easy, timely, informative, and accurate access to relevant and useful data. This forms the underlying framework and rationale for the learning content in BISM7206.ﾠ
This course provides students with an overall understanding of the relational database model and seeks to develop each student's ability to design and retrieve information from relational databases.
These skills will be further enhanced through learning Structured Query Language (SQL). The course seeks to develop students' knowledge and understanding of database elements, including data integrity, domains,ﾠrecovery, concurrency, security, and other similar concepts. Overall, students will learn how to: construct data models and normalised tables designed to help achieve business objectives; evaluate and apply integrity constraints, including domains, primary keys, and foreign keys; understand the concept of nulls and how this concept applies to SQL queries and database design; use SQL to retrieve relevant information for business purposes; andﾠunderstand the importance of database design elements in business applications. Students will also gain an appreciation of the benefits and requirements of distributed databases, and understand the relative advantages and disadvantages of relational and object-oriented databases and how these two models can coexist.
Course Changes in Response to Previous Student Feedback
1- AI-supported in-class exercises have been introduced, allowing students to complete parallel manual and GenAI-assisted SQL tasks to practise core coding skills, compare outputs, and experiment with prompt-engineering techniques.
2- Additional support for the team project is provided through an iteration submission for formative tutor feedback, as well as dedicated tutorial checkpoints where teams discuss progress and seek guidance.
Course requirements
Companion or co-requisite courses
You'll need to complete the following courses at the same time:
BISM7202 or MGTS7202 or 2 units of COMP/COMS/INFS courses
Incompatible
You can't enrol in this course if you've already completed the following:
BISM2207 or 3203 or INFS1200 or 7900 or 7901 or MGTS3203 or 7206
Restrictions
Quota: Minimum of 15 enrolments
Course contact
Course staff
Lecturer
Dr Reihaneh Bidar
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Please note: Teaching staff do not have access to the timetabling system to help with class allocation. Therefore, should you need help with your timetable and/or allocation of classes, please ensure you email business.mytimetable@uq.edu.au from your UQ student email account with the following details:
- Full name
- Student ID
- Course Code
Aims and outcomes
This course aims to provide students with an overall understanding of the relational database model. Important database concepts, methodologies, tools and techniques are introduced to provide students with the knowledge and skills to analyse, design and develop well-structured and effective databases. Students are introduced to data modelling techniques, entity relationship diagrams, and SQL to develop their ability to design and retrieve information from relational databases. The course also aims to enhance students' understanding of data integriety, domains, recovery, concurrency, security and other similar issues considered in the practical application of database management systems.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Demonstrate foundational understanding and/or critical application of data modelling techniques to design robust data structures that address complex business requirements.
LO2.
Apply SQL to extract data from relational information systems, and apply generative AI tools responsibly to support database design, coding and validation.
LO3.
Explain and apply principles of data quality assurance and apply techniques such as data cleaning, validation, and integrity enforcement to improve the reliability of organisational data.
LO4.
Apply current Information Systems issues and effectively communicate strategic recommendations for leveraging business data for competitive advantage.
LO5.
Collaborate effectively in teams and articulate complex information systems concepts through advanced written and oral communication skills.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution, Presentation, Role play/ Simulation |
AI debate
|
20% |
Week 6
During tutorial. |
| Computer Code, Paper/ Report/ Annotation |
Database design
|
40% |
Iteration Session Submission - not graded. 18/09/2026 4:00 pm Final Submission 23/10/2026 4:00 pm |
| Examination |
Assessment Task 3 - Final Exam
|
40% |
End of Semester Exam Period 7/11/2026 - 21/11/2026 |
Assessment details
AI debate
- Identity Verified
- In-person
- Mode
- Oral
- Category
- Participation/ Student contribution, Presentation, Role play/ Simulation
- Weight
- 20%
- Due date
Week 6
During tutorial.
- Other conditions
- Time limited, Secure.
- Learning outcomes
- L04
Task description
The objective of this assessment is to evaluate students’ ability to (1) demonstrate understanding of Information Systems issues, (2) critically reflect on and articulate the implications of AI for business processes and data use, and (3) engage constructively in informed discourse on the topics. While tutorial discussions will occur in groups, each student will be assessed individually. Detailed debate motions and preparation guidelines will be posted on Blackboard.
Preparation: You may use AI tools while researching and preparing written notes for the in-class debate. Use of AI tools is prohibited once the live debate begins.
Please note: The presentation will be recorded for marking purposes per UQ Policy.
Assessment security
Secure assessment: This assessment is designed to protect academic integrity and assess your understanding of course concepts. You must only use the approved materials and tools for this assessment task. Use of prohibited materials in this task may be investigated and treated as academic misconduct. See assessment instructions for more details.
Submission guidelines
More information will be released on Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
If you are unable to attend your presentation, please advise your Course Coordinator on or before the due date.
Database design
- Team or group-based
- Mode
- Product/ Artefact/ Multimedia, Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 40%
- Due date
Iteration Session Submission - not graded. 18/09/2026 4:00 pm
Final Submission 23/10/2026 4:00 pm
- Other conditions
- Peer assessed, Longitudinal.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
In this assessment, students will work in project teams of four (4) to five (5) members to analyse a provided client case study and design, develop, and implement a MySQL database system that meets the client’s business and data requirements. The project will culminate in the submission of a professional business report that includes modelling diagrams, supporting documentation, and SQL scripts, all created using MySQL Workbench.
This assessment task provides students with the opportunity to demonstrate:
- effective collaboration and teamwork skills;
- a solid understanding of core database concepts, and
- the ability to design, develop and implement a well-structured relational database that meets defined business requirements.
Tools: MySQL Workbench is required for this assessment. It can be downloaded from the UQ website, accessed via UQ’s Digital Workspace, or used directly in the BEL computer labs.
Iteration Session: Students will submit selected sections of their project by the end of Week 8. During the week 9 tutorial, students will receive oral feedback on their work from their tutor. This iteration submission is for feedback only and is not graded.
Teamwork: Assessment 2 will be undertaken in teams of 4–5 students. Team members must be enrolled in the same tutorial class to allow some teamwork to be conducted during tutorials. This is a mandatory requirement and is not open to negotiation. Students are reminded that a key Learning Objective of this course is the ability to work in teams, and this assessment task directly addresses that Learning Objective. Zero marks may apply if this requirement is not met.
Peer assessment: Students must submit confidential self and peer evaluations to assess team member contributions. The evaluation process assists the teaching team in understanding how each student contributed, and the findings are confidential. The peer evaluation may affect each student's mark for this assignment.
Further Information: Assessment guidelines, team requirements, the case study description, marking rubric, and specifications will be available under the Assessment link on Blackboard.
Assessment security
Open assessment: In this assessment you can use resources such as your notes, course materials, and other tools, including AI, while completing the task. The focus is not on memorising information, but on understanding, applying judgement, and demonstrating your own thinking.
Submission guidelines
Submissions must be uploaded through the provided Blackboard links. Please follow the detailed instructions provided on Blackboard for further information.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
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.
Assessment Task 3 - Final Exam
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
7/11/2026 - 21/11/2026
- Other conditions
- Time limited, Secure.
- Learning outcomes
- L01, L02, L03, L04
Task description
The Final Examination will consist of multiple choice, short answer and problem-solving questions based on learning materials presented in lectures, tutorials and the relevant chapters of the textbook from week 1 to week 13 inclusive.
Further details about the exam will be discussed in lectures and posted to the Blackboard course site.
Assessment security
Secure assessment: This assessment is designed to protect academic integrity and assess your understanding of course concepts. You must only use the approved materials and tools for this assessment task. Use of prohibited materials in this task may be investigated and treated as academic misconduct. See assessment instructions for more details.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 90 minutes |
| Calculator options | No calculators permitted |
| Open/closed book | Closed book examination - no written materials 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 Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 29 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30 - 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 will be allocated according to University-wide standards of criterion-based assessment.
Supplementary assessment
Supplementary assessment is available for this course.
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 |
|---|---|---|
Week 1 |
Lecture |
Course Overview and Intro to DBMS Introduction to database management, including traditional file-based systems, the database management system and fundamental database concepts. Readings/Ref: CB (Ch. 1, 2) Learning outcomes: L01, L04 |
Week 2 |
Lecture |
Entity Relationship Modelling Entity relationship modelling is explored in terms of a data driven approach using entity-relationship diagrams including design elements such as entities, relationships, attributes, keys and multiplicity. Readings/Ref: CB (Ch. 12 and 13) Learning outcomes: L01, L04 |
Tutorial |
Tutorial 1: Data & Information; MYSQL prep Students will explore the difference between data and information, examine the 3-level database architecture through discussion and case analysis, and begin preparing for practical database work by setting up and navigating the MySQL environment. Learning outcomes: L01, L04 |
|
Week 3 |
Lecture |
Relational Model Relational model concepts are discussed including specific terminology, keys, views and integrity constraints. Readings/Ref: CB (Ch. 4) Learning outcomes: L01, L03 |
Tutorial |
Tutorial 2: Entity Relationship Modelling Students will identify entities and relationships in real-world scenarios, review key concepts such as multiplicity and participation constraints, and apply their understanding through practical ER modelling exercises. Ekka Public Holiday - Wednesday 12th August 2026 - Check Blackboard for announcements about affected classes. Learning outcomes: L01, L04 |
|
Week 4 |
Lecture |
Structured Query Language (I) Introduction to basic SQL DDL and DML statements. Readings/Ref: CB (Ch. 6,7) Learning outcomes: L02 |
Tutorial |
Tutorial 3: Relational Modelling Students will work through practical exercises on relations, keys, and integrity constraints, and apply these concepts by creating a relational model and corresponding relational schema. Learning outcomes: L01, L03 |
|
Week 5 |
Lecture |
Structured Query Language (II) Exploring aggregation and grouping, and relational operations to enable search conditions and order/grouping of results. Readings/Ref: CB (Ch. 6,7) Learning outcomes: L02 |
Tutorial |
Tutorial 4: SQL Pactical Exercises (1) This tutorial focuses on foundational SQL skills through practical exercises in MySQL, starting with basic queries and manual command-line operations. Students will then engage in AI-assisted prompt engineering to generate, interpret, and refine SQL queries. Learning outcomes: L02 |
|
Week 6 |
Lecture |
AI Debate Week – No Lecture Learning outcomes: L01, L04 |
Tutorial |
Tutorial 5: In-class AI debate (Assignment 1) This tutorial is dedicated to Assignment 1, where students will participate in an in-class AI debate, critically examining the role of AI in data management and information systems. Learning outcomes: L01, L04 |
|
Week 7 |
Lecture |
Normalisation Explore how normalisation supports database design and how concepts such as partial, transitive, and functional dependencies enable the logical database design to transition and conform to particular normal forms. Readings/Ref: CB (Ch. 14,15) Learning outcomes: L02 |
Tutorial |
Tutorial 6: SQL practices (II) This tutorial focuses on advancing SQL skills using MySQL Workbench, with an emphasis on tackling complex queries and clarifying challenging concepts. Students will also explore AI-assisted prompt engineering to generate and refine advanced SQL queries, enhancing their problem-solving and query optimization abilities. Learning outcomes: L03 |
|
Week 8 |
Lecture |
Data Quality and Cleaning Data is a valuable resource and access to accurate, current and informative data is critical to business success. Therefore, data needs to be managed and organised like other business assets. Learning outcomes: L03 |
Tutorial |
Tutorial 7: Normalisation exercises Students will engage in practical exercises to identify functional dependencies and apply normalization techniques up to 3NF, reinforcing their understanding of data structure optimization and redundancy reduction. Learning outcomes: L02 |
|
Week 9 |
Lecture |
Guest Lecture Learning outcomes: L01, L02, L04 |
Tutorial |
Tutorial 8: Assignment Iteration feedback and Data cleaning This tutorial focuses on providing feedback on Assignment 1 iterations and developing data cleaning skills. Students will identify and resolve common data quality issues to prepare datasets for accurate analysis and reporting. Learning outcomes: L02, L03, L04, L05 |
|
Mid-sem break |
No student involvement (Breaks, information) |
In-Semester Break |
Week 10 |
Lecture |
Transaction Management This lecture explores the critical role of transaction management in business systems, focusing on how organisations maintain data integrity and consistency in multi-user environments and recover from failures to ensure reliable operations. Readings/Ref: CB (Ch. 22) Learning outcomes: L01, L04 |
Tutorial |
Tutorial 9: Team project This tutorial is dedicated to the team project, providing students with structured time to work in their groups, develop project deliverables. Learning outcomes: L01, L04, L05 |
|
Week 11 |
Lecture |
Database Security and Control We’ll look at why database security matters, the main threats to data security, and the core ideas of confidentiality, integrity, and availability (the CIA triad). We’ll also cover practical countermeasures and finish with an overview of Data Control Language (DCL). Readings/Ref: CB (Ch. 20) Learning outcomes: L01, L02 |
Tutorial |
Tutorial 10: Database Security and team project This tutorial covers practical exercises in database security, focusing on access control and user permissions. Students will also continue working on their team projects. Learning outcomes: L01, L02, L04, L05 |
|
Week 12 |
Lecture |
Distributed Database Management Systems We examine distributed DBMSs including concepts, problems, technologies and protocols. Readings/Ref: CB (Ch. 24, 25) Learning outcomes: L01, L04 |
Tutorial |
Tutorial 11: Team Project This tutorial is dedicated to the team project, providing students with structured time to work in their groups, develop project deliverables, and receive feedback on their progress. Learning outcomes: L02, L03, L04, L05 |
|
Week 13 |
Lecture |
Overview and Big Data & Technologies Exploring why data management technologies and approaches have expanded beyond relational databases and data warehousing. Learning outcomes: L01, L04 |
Tutorial |
Tutorial 12: Exam consult Learning outcomes: L01, L02, L03, L04 |
Additional learning activity information
This tutorial is dedicated to exam consultation and problem-solving exercises. Students will practice sample questions and clarify any remaining uncertainties to prepare effectively for the final assessment.
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 for Students Policy and Procedure
- AI for Assessment Guide
- Recording of Teaching Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.