Course coordinator
Associate Professor Sen Wang
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Distributed database design, query and transaction processing, data integration, data warehousing, data cleansing, management of spatial data, and data from large scale distributed devices.
Most contemporary information systems are built to derive value from very large amounts of dynamic data from different sources with high efficiency, high scalability, and low cost. This course builds on students' previous knowledge of centralised information systems to introduce advanced technologies and their design issuesﾠincluding data warehousing for online analytical processing, dataﾠintegration for combining heterogeneousﾠand oftenﾠunstructuredﾠdata fromﾠdifferentﾠsources, and data quality management forﾠensuringﾠtheﾠfitness of data for use. Data security and privacy issues will be discussed. The course also looks at related topics ofﾠemerging platforms for managing large-scale or "big" data. Based on student feedback, the course materials, including lecture notes, tutorials, and practical sessions, have been revised and enhanced for improved quality.
Course requirements
Assumed background
Background knowledge: database management systemﾠarchitecture, relational database design and indexing,ﾠquery processing and optimization, transaction management, concurrency control, recovery, SQL view.ﾠ
Programming skills: SQL and Java (or SQL andﾠPython).ﾠ
Prerequisites
You'll need to complete the following courses before enrolling in this one:
INFS2200
Incompatible
You can't enrol in this course if you've already completed the following:
INFS7907
Course contact
Course staff
Lecturer
Associate Professor Sen Wang
Professor Shazia Sadiq
Dr Zhi Chen
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
To provide an understanding of the issues involved in designing and implementing large scale data intensive applications. To equip the students with sufficient conceptual and practical knowledge, to be able to recognize the challenges, analyze the appropriateness of the technology and understand the design and implementation complexities.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Distinguish and classify the main architectures in large scale database systems including centralized, distributed and multi-databases.
LO2.
Develop insights into issues and challenges in data integration including data quality control, data cleansing, and design and construction of data warehouses.
LO3.
Relate your conceptual and practical knowledge in advanced database systems to past knowledge as well as emerging trends including implications of big data.
LO4.
Understand and analyze post-relational database models and advanced issues related to data integration, data quality, and data privacy.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Computer Code, Practical/ Demonstration | Practicals - 1 | 10% |
30/08/2024 3:00 pm |
| Examination |
In-Semester Exam
|
30% |
17/09/2024
The in-semester exam will be taken during the lecture in Week 9. More information about the arrangement will be announced. |
| Computer Code, Practical/ Demonstration | Practicals - 2 | 10% |
18/10/2024 3:00 pm |
| Examination |
Final Exam
|
50% |
End of Semester Exam Period 2/11/2024 - 16/11/2024 |
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
Practicals - 1
- Mode
- Written
- Category
- Computer Code, Practical/ Demonstration
- Weight
- 10%
- Due date
30/08/2024 3:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
There are several practical tasks. Students may complete the task earlier than the due deadline and have it marked off.
Submission guidelines
Online Submission.
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.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students within 14-21 days, where the earlier time frame applies if there are no extensions.
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.
In-Semester Exam
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 30%
- Due date
17/09/2024
The in-semester exam will be taken during the lecture in Week 9. More information about the arrangement will be announced.
- Learning outcomes
- L01, L02, L03, L04
Task description
The in-semester exam is a school-based 90-minute closed-book examination. It will be held and invigilated during lecture time in Week 9. The covered topics range from Week 2 to Week 8.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 90 minutes |
| Calculator options | Any calculator 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.
Information about the location and time of the deferred in-semester exam will be announced.
Practicals - 2
- Mode
- Written
- Category
- Computer Code, Practical/ Demonstration
- Weight
- 10%
- Due date
18/10/2024 3:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
There are several practical tasks. Students may complete the task earlier than the due deadline and have it marked off.
Submission guidelines
Online Submission.
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.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students within 14-21 days, where the earlier time frame applies if there are no extensions.
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
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
- Learning outcomes
- L01, L02, L03, L04
Task description
The final closed-book examination will cover all course topics.
Students will sit an on-campus invigilated exam.
Hurdle requirements
Students must achieve at least 50% on the final exam in order to pass this course (i.e., at least 25 marks out of 50). If you achieve less than 50% in the final examination, your overall final marks 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 - 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 - 19 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 20 - 44 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45 - 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
Students must achieve at least 50% on the final exam in order to pass this course (i.e., at least 25 marks out of 50). If you achieve less than 50% in the final examination, your overall final marks will be capped at 49, and your final grade will be capped at 3.
Note that your final percentage will be rounded to the nearest whole number (e.g. 84.5% is a 7), and the final marks are calculated as a simple accumulation of all marks obtained in this semester.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Use of Artificial Intelligence or Machine Translation
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 technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
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.
Additional learning resources information
A number of research and industry articles will be provided as additional reading materialsﾠfor specific topics. These will be made available on the course 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 |
Practical |
Lab-based Practicals Learning outcomes: L01, L02, L03, L04 |
Multiple weeks From Week 1 To Week 13 |
Lecture |
Weekly Lecture Presentations Learning outcomes: L01, L02, L03, L04 |
Multiple weeks From Week 2 To Week 12 |
Tutorial |
Tutorials 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 - 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: