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Course profile

Managing Business Data (BISM2207)

Study period
Sem 1 2025
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 1, 2025 (24/02/2025 - 21/06/2025)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Business School

This course aims to develop students' ability to manage and retrieve information from Information Systems. Students will learn how to use Structured Query Language (SQL) to retrieve information critical for business decision making, and will also develop a thorough understanding of data integrity and its effects on the quality of business decisions. The course also provides a hands-on experience with conceptual modelling of data requirements for business. This course further enhances the students' employability in other areas such as the ability to work in teams, the ability to think analytically and critically, and build confidence in presenting professionally.

This course provides students with an overall understanding of the relational database model. It emphasizes the SQL query language and seeks to develop students' ability to design and retrieve information from relational databases. The course informs students of database elements including domains, nulls, recovery, concurrency, security, and other similar issues. As such, students will learn how to: use the SQL query language to retrieve relevant information for business purposes; construct semantic data models to help achieve business objectives and know how to convert these models into normalized tables; 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; understand the importance of the database elements in their application; gain an appreciation of the benefits and requirements of distributed databases.

Course requirements

Assumed background

As the course will be both theoretical and practical ("hands on"), students are expected to be comfortable using PC applications as well as having a good understanding of how business users utilise computer database applications to automate and enhance their business applications. As the assignment will be project based and managed through a project team environment, it is expected that students are familiar and comfortable with this style of contribution to their learning and assessment.

Before attempting this course, students are advised that it is important to complete the appropriate prerequisite course(s) listed on the front of this course profile. No responsibility will be accepted by the School of Business, the Faculty of Business, Economics and Law or the University of Queensland for poor student performance occurring in courses where the appropriate prerequisite(s) has/have not been completed, for any reason whatsoever.

Prerequisites

You'll need to complete the following courses before enrolling in this one:

BISM1201 or 2 units COMP/COMS/INFS courses

Incompatible

You can't enrol in this course if you've already completed the following:

BISM3203 or 7206 or INFS1200 or 7900 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. In doing so, it emphasises the SQL query language and seeks to develop each student's ability to design and retrieve information from relational databases. The course also aims to make students aware of domains, nulls, recovery, concurrency, security, and other similar issues. This course further enhances the students' employability in other areas such as the ability to workᅠin teams, the ability to thinkᅠanalyticallyᅠand critically, and build confidence in presenting professionally.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Understand and apply popular data modelling techniques and develop appropriate data structures for particular business environments.

LO2.

Understand and apply the structured query language (SQL) to extract data from relational information systems.

LO3.

Develop and apply data quality assurance procedures to improve data quality.

LO4.

Research and understand current Information Systems issues and identify how to exploit available data for corporate advantage.

LO5.

Build your ability to work in teams and develop written presentation skills, which are regarded as essential to the effective and efficient conduct of information systems development projects in organisations.

Assessment

Assessment summary

Category Assessment task Weight Due date
Examination, Quiz Quiz
  • Online
20%

Week 6

During Lecture time

Paper/ Report/ Annotation, Product/ Design, Project System Development
  • Team or group-based
40%

23/05/2025 6:00 pm

Peer Assessment due 1 week after the assessment due date.

Examination Final Exam
  • Identity Verified
  • In-person
40%

End of Semester Exam Period

7/06/2025 - 21/06/2025

Assessment details

Quiz

  • Online
Mode
Written
Category
Examination, Quiz
Weight
20%
Due date

Week 6

During Lecture time

Other conditions
Time limited.

See the conditions definitions

Learning outcomes
L01, L02, L03

Task description

The online quiz will take place during the Week 6 lecture time. The quiz will be 60 minutes long. This assessment task covers learning materials presented in lectures, tutorials and the relevant textbook chapters from week 1 to week 5 inclusive. Further information about the exam will be presented during lectures. 

AI Statement:

Note: This assessment task evaluates students' abilities, skills, and knowledge without the aid of generative Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Exam details

Planning time no planning time minutes
Duration 60 minutes
Calculator options

Any calculator permitted

Open/closed book Open Book examination
Exam platform Other
Invigilation

Not invigilated

Submission guidelines

Deferral or extension

You may be able to defer this exam.

Late submission

Exams submitted after the end of the submission time will incur a late penalty.

System Development

  • Team or group-based
Mode
Product/ Artefact/ Multimedia
Category
Paper/ Report/ Annotation, Product/ Design, Project
Weight
40%
Due date

23/05/2025 6:00 pm

Peer Assessment due 1 week after the assessment due date.

Other conditions
Peer assessed, Longitudinal.

See the conditions definitions

Learning outcomes
L01, L02, L03, L04, L05

Task description

The main purpose of this assessment is to develop your ability to work in a team and to design, develop, and implement a well-structured relational database that effectively supports the given scenario. Students will be required to demonstrate their knowledge and ability to use SQL. The fundamental knowledge and skills required for this assessment task are expected to be cultivated through lectures and tutorials. However, students will need to conduct additional research to further enhance the skills necessary to successfully complete this assessment.

Team formation and teamwork: You will undertake this project as a part of a team of 3 to 5 members. Project team members must be allocated to the same tutorial. You will submit portions of the project at intervals, receive oral comments on your work during the informal presentations from your tutor, and revise earlier submissions.

Feedback on draft submissions (iterations 1 and 2): You will submit portions of the project at intervals (two draft points/iterations), receive oral comments on your work, and revise earlier submissions accordingly. These submissions are for feedback only and are not graded.

  • Iteration 1 during week 8 tutorials. The submission due date will be announced on Blackboard.
  • Iteration 2 during week 11 tutorials. The submission due date will be announced on Blackboard.

Peer Assessment: students will be required to complete a self and peer evaluation as part of this assignment. 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. A link will be provided on Blackboard for this evaluation. 

Working effectively in a Team: A Practical Guide MOOC explores ways in which to learn how to build effective teams, be a great team player, and manage team conflict. You are encouraged to complete this practical guide if you haven't done a team project before. Refer to Teams101x MOOC.

AI Statement:

This task has been designed to be challenging, authentic, and complex. Whilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submissions independent of AI tools. If AI has been used it must be acknowledged.

Submission guidelines

Submit through Blackboard Assessment links.

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.

Final Exam

  • Identity Verified
  • In-person
Mode
Written
Category
Examination
Weight
40%
Due date

End of Semester Exam Period

7/06/2025 - 21/06/2025

Other conditions
Time limited.

See the conditions definitions

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 evaluates students' abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and 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

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

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Learning period Activity type Topic
Week 1
Lecture

Course Overview and Intro to DBMS

Learning outcomes: L01, L04

Week 2
Lecture

Entity-Relationship Model

Learning outcomes: L01

Tutorial

T1: Data & Infomration and SQL prep

Learning outcomes: L01, L04

Week 3
Lecture

Relational Model

Learning outcomes: L01, L03

Tutorial

T2: Entity-Relationship Model

Learning outcomes: L01

Week 4
Lecture

Database Design and Structured Query Language (I)

Learning outcomes: L01, L02, L03

Tutorial

T3: Relational Model

Learning outcomes: L01, L03

Week 5
Lecture

Structured Query Language (II)

Learning outcomes: L02, L03, L05

Tutorial

T4: SQL Exercises

Learning outcomes: L02, L03

Week 6
Lecture

In-Semester Quiz

In Semester Quiz during Lecture Time.

Tutorial

T5: SQL Exercises

Learning outcomes: L02, L03

Week 7
Lecture

Normalisation

Learning outcomes: L01, L03, L04

Tutorial

T6: SQL Exercises

Learning outcomes: L01, L02, L03, L04

Week 8
Lecture

Data Quality and Cleaning, and Presentation Skills

Learning outcomes: L01, L03, L04

Tutorial

T7: Project Iteration 1 Presentation and Normalisation Exercises

Learning outcomes: L01, L02, L03, L04, L05

Mid-sem break
No student involvement (Breaks, information)

In-Semester Break

Week 9
Lecture

Transaction Management: Recovery and Concurrency

Learning outcomes: L01, L04

Tutorial

T8: Practical Exercises for Normalisation 

Learning outcomes: L01, L03, L04

Week 10
Lecture

Labour Day Public Holiday

Tutorial

T9: SQL exercises- Recovery and Concurrency

Labour Day Public Holiday - Monday 5 May 2025 - Check Blackboard for announcements about affected classes.

Learning outcomes: L01, L02, L04

Week 11
Lecture

Datbase Security and Control

Learning outcomes: L01, L03, L04

Tutorial

T10: Project Iteration 2 Presentation

Learning outcomes: L01, L02, L03, L04, L05

Week 12
Lecture

Distributed DBMS

Learning outcomes: L01, L04

Tutorial

T11: Team Project

Learning outcomes: L01, L02, L03, L04, L05

Week 13
Lecture

Big Data and Intelligence Technologies

Learning outcomes: L01, L04

Tutorial

T12: Q&A and Exam Practice

Learning outcomes: L01

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:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.