Course coordinator
Dr Reihaneh Bidar
Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
Data analysis, design and policy issues in business situations. Business issues in relation to database management, conceptual modelling, and data modelling in business applications. Using structured Query Language (SQL) to uncover critical information for business decision making. Business intelligence via data warehousing and data mining. Applications of database systems in a business context. Critical analysis and discussion of recent business research into database systems.
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.
Students will learn to use AI tools such as Gemini to support code generation, prompt engineering, and the validation of SQL queries. They will also learn to transform complex database questions into accurate SQL queries through AI-guided exploration and develop the skills needed to use AI responsibly in data management.
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.
Understand and apply Structured Query Language (SQL) to extract data from relational information systems.
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.
Identify and analyse current Information Systems issues and suggest strategic approaches to 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 Time. |
| Paper/ Report/ Annotation, Practical/ Demonstration, Product/ Design, Project |
Team Project- Database design
|
40% |
Iteration Session Submission - not graded. 19/09/2025 4:00 pm Final Submission 24/10/2025 4:00 pm |
| Examination |
Assessment Task 3 - Final Exam
|
40% |
End of Semester Exam Period 8/11/2025 - 22/11/2025 |
Assessment details
AI debate
- In-person
- Mode
- Oral
- Category
- Participation/ Student contribution, Presentation, Role play/ Simulation
- Weight
- 20%
- Due date
Week 6
During tutorial Time.
- Learning outcomes
- L04, L05
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 teams, each student will be assessed individualy. Detailed debate motions and preparation guidelines will be posted on Blackboard.
Preparation: You may consult 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.
AI Statement:
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
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 7 days. Extensions are given in multiples of 24 hours.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Late submissions are not permitted. If you require additional time, you must lodge a formal extension request via the UQ website before the scheduled assessment date.
Team Project- Database design
- Team or group-based
- Mode
- Product/ Artefact/ Multimedia, Written
- Category
- Paper/ Report/ Annotation, Practical/ Demonstration, Product/ Design, Project
- Weight
- 40%
- Due date
Iteration Session Submission - not graded. 19/09/2025 4:00 pm
Final Submission 24/10/2025 4:00 pm
- Other conditions
- Peer assessed.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
This assessment task provides students with the opportunity to demonstrate:
- effective collaboration and teamwork skills;
- demonstrate their understanding of database concepts; and
- their ability to design, develop and implement a well-structured relational database that effectively supports the given case study business requirements
Students will also be required to demonstrate their knowledge and ability to use SQL. While it is anticipated that the fundamental knowledge and skills will be developed through lecture and tutorial materials, students will be required to undertake additional research to further develop the skills required to successfully complete this assessment task.
Students are required to submit a professional business report including professional modelling diagrams, supporting documentation and SQL scripts for drawing models (freely available on the Web). SQL scripts are to be created using MySQL Workbench software, which is available on UQ's "Digital Workspace" or Virtual Machine and in the BEL labs.
Iteration Session (Week 8): Students will submit selected sections of their project by the end of Week 8. During week 9 tutorial, students receive oral comments on their work from their tutor. This iteration submission is for feedback only and is not graded.
Teamwork:
Assessment Task 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 will not be 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 will apply if this requirement is not addressed.
Peer assessment:
Students must submit confidential self and peer evaluations to enable assessment of team member contributions. The evaluation process assists the teaching team to understand how each student contributed, and the findings are confidential. The peer evaluation can affect each student's mark for this assignment.
Assessment guidelines, along with team requirements, the case study description, marking rubric, and specifications will be available under the Assessment link on Blackboard.
AI Statement:
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
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.
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
8/11/2025 - 22/11/2025
- 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.
AI Statement:
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
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
Library resources are available 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. 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. Learning outcomes: L01, L04 |
Tutorial |
Tutorial 1: Data & Information; MYSQL prep Difference between data and information; importance of data and information; 3-level architecture; database case study. Learning outcomes: L01, L04 |
|
Week 3 |
Lecture |
Relational Model Relational model concepts are discussed including specific terminology, keys, views and integrity constraints. Learning outcomes: L01, L03 |
Tutorial |
Tutorial 2: Entity Relationship Modelling Identify entities and relationships; review multiplicity and other relevant concepts; ERM practical exercises. EKKA Public Holiday - Wednesday 13 August 2025 - 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. Learning outcomes: L02 |
Tutorial |
Tutorial 3: Relational Modelling Practical exercises and concepts - relations, keys, integrity constraints; create a relational model and relational schema. Learning outcomes: L01, L03 |
|
Week 5 |
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. Learning outcomes: L03 |
Tutorial |
Tutorial 4: SQL Pactical Exercises SQL practical exercises. 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 week’s tutorial will be devoted to Assignment 1: an in-class AI debate. Learning outcomes: L04, L05 |
|
Week 7 |
Lecture |
Structured Query Language (II) Exploring aggregation and grouping, and relational operations to enable search conditions and order/grouping of results. Learning outcomes: L02 |
Tutorial |
Tutorial 6: Normalisation exercises Practical exercises on dependencies and normalisation concepts. 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: SQL practices Learning outcomes: L02 |
|
Week 9 |
Lecture |
Transaction Management Learning outcomes: L01, L02, L04 |
Tutorial |
Tutorial 8: Assignment Iteration feedback and presentations Learning outcomes: L02, L03, L04, L05 |
|
Mid Sem break |
No student involvement (Breaks, information) |
In-Semester Break |
Week 10 |
Lecture |
Data Warehousing We expand our knowledge of database applications with an introduction to data warehousing and data integration. Learning outcomes: L01, L04 |
Tutorial |
Tutorial 9: Transaction Management Learning outcomes: L01, L04 |
|
Week 11 |
Lecture |
Database Security and Control 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: L01, L02 |
Tutorial |
Tutorial 10: Database Security Pactical Exercises Learning outcomes: L01, L02, L04 |
|
Week 12 |
Lecture |
Distributed Database Management Systems We examine distributed DBMSs including concepts, problems, technologies and protocols. Learning outcomes: L01, L04 |
Tutorial |
Tutorial 11: Team Project 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 |
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
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.