DSB201 Advanced Databases
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | DSB201 |
|---|---|
| Prerequisite(s): | (IFB104 or ITD104 or EGB103) and (IFB105 or IFB130 or ITD105) |
| Equivalent(s): | IAB206 |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,192 |
| Domestic tuition unit fee | $4,704 |
| International unit fee | $5,640 |
Unit Outline: Semester 2 2026, Gardens Point, Internal
| Unit code: | DSB201 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | (IFB104 or ITD104 or EGB103) and (IFB105 or IFB130 or ITD105) |
| Equivalent: | IAB206 |
| Coordinator: | Sareh Sadeghianasl | s.sadeghianasl@qut.edu.au |
Overview
This unit introduces you to the technologies that can be used to address challenges in managing fast incoming, voluminous, and varied data that is increasingly being relied on to make decisions in today's business environment. You will develop practical skills in using advance database technologies that will prepare you to be a data analyst, business analyst, solution architect, as well as enterprise architect.
Learning Outcomes
On successful completion of this unit you will be able to:
- Describe key issues for modern data management and identify corresponding technologies to address the issues, independent of any specific platform or framework.
- Evaluate various capabilities of advanced databases technologies.
- Design and develop solutions to support data analysis using advanced database technologies.
- Collaborate with others to efficiently manage and deliver on projects related to the development of advanced database solutions for a client.
- Communicate advanced database solutions effectively to clients.
Content
This unit will introduce concepts and techniques needed to manage today's data at various stages of its use, including those technologies that can be used to (1) store and retrieve data at rest which may come in various formats using modern database technologies (such as NoSQL databases); (2) apply the necessary treatment of data while it is in-transit, such as streaming data processing and distributed ledger; and, (3) process a large volume of data using a parallel and distributed programming style (e.g. map-reduce algorithm and in-memory database). Furthermore, this unit also introduces fundamentals of modern data management concepts, such as transactional properties of a database and the structuredness (or lack thereof) of today's data. You will be introduced to the top NoSQL databases being used in industry. You are encouraged to gain key skills for learning including communication, academic writing, and teamwork. You will have guest lecture(s) from industry showcasing their best practices in designing, maintaining, and analysing advanced database solutions, providing networking and prospective career paths. You will receive formative feedback on your progress in the hands-on tutorials.
Learning Approaches
The content of this unit will be delivered through a combination of pre-recorded lectures and computer tutorials. In addition to the QUT Canvas site, online messaging platform, such as Slack, will be used. Pre-recorded lectures will cover the theoretical aspects of the unit, while the tutorials will provide the opportunity for you to reinforce the knowledge you have learned from lectures by putting it into practice. A hands-on approach to learning is used whereby concepts learned are illustrated through worked examples and demonstrations. You are encouraged to work in groups to foster your ability to perform as part of a development team. You are encouraged to discuss the difficulties that you face in solving assessment tasks with your group partner(s).
Feedback on Learning and Assessment
Feedback for the assignment will be provided to support further learning. Students will receive formal feedback on the assessment task from their tutor prior to the exam. Teaching staff are available during the tutorials and consultation hours to clarify or elaborate on the assignment contents and to provide constructive feedback.
Assessment
Overview
The assessments in this unit measure your ability to apply knowledge related to advanced database technologies to address real-world scenarios informed by contemporary industry-based problems. The assessment of this unit consists of one Project to be completed during the teaching period and an Examination (invigilated) to be completed during the central examination period. The project is to be completed in a group with some individual components. The project is to be submitted electronically through Canvas.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: NoSQL Database Design and Analysis
This group assignment will require you to create and retrieve data from a NoSQL database using queries. You will be asked to model and implement a NoSQL database based on a realistic industry-informed scenario using an open-source NoSQL platform. You will be asked to formulate queries to retrieve frequently-accessed information from your database. You are expected to provide a comprehensive report detailing the outcomes of this project. An individual interview about your project will take place after its submission. The ethical and responsible use of generative artificial intelligence (GenAI) tools is authorised in this assessment. See the relevant assessment details in Canvas for specific guidelines.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
This is an in-person exam that evaluates your understanding of key concepts, techniques, challenges and trade-offs related to advanced databases explored in lectures and tutorials. This exam is invigilated, and you will be required to attend the campus or an assessment centre. The use of generative artificial intelligence (GenAI) tools is prohibited during this assessment.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Requirements to Study
Costs
No extraordinary charges or costs are associated with the requirements for this unit.
Resources
This unit does not have a required textbook, but below is a list of recommended readings that can be sourced via the library. All other learning material is available in the unit Canvas site.
Resource Materials
Recommended text(s)
Joe Celko. Joe Celko's Complete Guide to NoSQL: What Every SQL Professional Needs to Know about Non-Relational Databases. Morgan Kaufmann, Boston, 2014
Jure Leskovec, Anand Rajaraman, and Jeffrey D. Ullman. Mining of Massive Datasets. Stanford University. 2014.
Roger Wattenhofer. Distributed Ledger Technology: The Science of the Blockchain. CreateSpace Independent Publishing Platform. 2017.
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with studying this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.DS01 Bachelor of Data Science
- Demonstrate a broad and coherent knowledge of the principles, concepts and techniques of the data science discipline, with depth of knowledge in at least one area developed through a major.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Use appropriate statistical, computational, modelling, data management, programming and generative artificial intelligence techniques to develop solutions for deriving insights from data.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Demonstrate critical thinking and problem-solving skills, as well as adaptivity in applying learned techniques in new and unfamiliar contexts.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Work effectively both independently and collaboratively in diverse and interdisciplinary teams.
Relates to: NoSQL Database Design and Analysis - Communicate effectively in a variety of modes, to expert and non-expert audiences, including in a professional context.
Relates to: NoSQL Database Design and Analysis
IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: NoSQL Database Design and Analysis - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: NoSQL Database Design and Analysis - Communicate professionally and effectively in written, verbal and visual formats to a diverse range of stakeholders, considering the audience and explaining complex ideas in a simple and understandable manner in a range of IT-related contexts.
Relates to: NoSQL Database Design and Analysis
Unit Outline: Semester 2 2026, Online
| Unit code: | DSB201 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | (IFB104 or ITD104 or EGB103) and (IFB105 or IFB130 or ITD105) |
| Equivalent: | IAB206 |
Overview
This unit introduces you to the technologies that can be used to address challenges in managing fast incoming, voluminous, and varied data that is increasingly being relied on to make decisions in today's business environment. You will develop practical skills in using advance database technologies that will prepare you to be a data analyst, business analyst, solution architect, as well as enterprise architect.
Learning Outcomes
On successful completion of this unit you will be able to:
- Describe key issues for modern data management and identify corresponding technologies to address the issues, independent of any specific platform or framework.
- Evaluate various capabilities of advanced databases technologies.
- Design and develop solutions to support data analysis using advanced database technologies.
- Collaborate with others to efficiently manage and deliver on projects related to the development of advanced database solutions for a client.
- Communicate advanced database solutions effectively to clients.
Content
This unit will introduce concepts and techniques needed to manage today's data at various stages of its use, including those technologies that can be used to (1) store and retrieve data at rest which may come in various formats using modern database technologies (such as NoSQL databases); (2) apply the necessary treatment of data while it is in-transit, such as streaming data processing and distributed ledger; and, (3) process a large volume of data using a parallel and distributed programming style (e.g. map-reduce algorithm and in-memory database). Furthermore, this unit also introduces fundamentals of modern data management concepts, such as transactional properties of a database and the structuredness (or lack thereof) of today's data. You will be introduced to the top NoSQL databases being used in industry. You are encouraged to gain key skills for learning including communication, academic writing, and teamwork. You will have guest lecture(s) from industry showcasing their best practices in designing, maintaining, and analysing advanced database solutions, providing networking and prospective career paths. You will receive formative feedback on your progress in the hands-on tutorials.
Learning Approaches
The content of this unit will be delivered through a combination of pre-recorded lectures and computer tutorials. In addition to the QUT Canvas site, online messaging platform, such as Slack, will be used. Pre-recorded lectures will cover the theoretical aspects of the unit, while the tutorials will provide the opportunity for you to reinforce the knowledge you have learned from lectures by putting it into practice. A hands-on approach to learning is used whereby concepts learned are illustrated through worked examples and demonstrations. You are encouraged to work in groups to foster your ability to perform as part of a development team. You are encouraged to discuss the difficulties that you face in solving assessment tasks with your group partner(s).
Feedback on Learning and Assessment
Feedback for the assignment will be provided to support further learning. Students will receive formal feedback on the assessment task from their tutor prior to the exam. Teaching staff are available during the tutorials and consultation hours to clarify or elaborate on the assignment contents and to provide constructive feedback.
Assessment
Overview
The assessments in this unit measure your ability to apply knowledge related to advanced database technologies to address real-world scenarios informed by contemporary industry-based problems. The assessment of this unit consists of one Project to be completed during the teaching period and an Examination (invigilated) to be completed during the central examination period. The project is to be completed in a group with some individual components. The project is to be submitted electronically through Canvas.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: NoSQL Database Design and Analysis
This group assignment will require you to create and retrieve data from a NoSQL database using queries. You will be asked to model and implement a NoSQL database based on a realistic industry-informed scenario using an open-source NoSQL platform. You will be asked to formulate queries to retrieve frequently-accessed information from your database. You are expected to provide a comprehensive report detailing the outcomes of this project. An individual interview about your project will take place after its submission. The ethical and responsible use of generative artificial intelligence (GenAI) tools is authorised in this assessment. See the relevant assessment details in Canvas for specific guidelines.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
This is an in-person exam that evaluates your understanding of key concepts, techniques, challenges and trade-offs related to advanced databases explored in lectures and tutorials. This exam is invigilated, and you will be required to attend the campus or an assessment centre. The use of generative artificial intelligence (GenAI) tools is prohibited during this assessment.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Requirements to Study
Costs
No extraordinary charges or costs are associated with the requirements for this unit.
Resources
This unit does not have a required textbook, but below is a list of recommended readings that can be sourced via the library. All other learning material is available in the unit Canvas site.
Resource Materials
Recommended text(s)
Joe Celko. Joe Celko's Complete Guide to NoSQL: What Every SQL Professional Needs to Know about Non-Relational Databases. Morgan Kaufmann, Boston, 2014
Jure Leskovec, Anand Rajaraman, and Jeffrey D. Ullman. Mining of Massive Datasets. Stanford University. 2014.
Roger Wattenhofer. Distributed Ledger Technology: The Science of the Blockchain. CreateSpace Independent Publishing Platform. 2017.
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with studying this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.DS01 Bachelor of Data Science
- Demonstrate a broad and coherent knowledge of the principles, concepts and techniques of the data science discipline, with depth of knowledge in at least one area developed through a major.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Use appropriate statistical, computational, modelling, data management, programming and generative artificial intelligence techniques to develop solutions for deriving insights from data.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Demonstrate critical thinking and problem-solving skills, as well as adaptivity in applying learned techniques in new and unfamiliar contexts.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Work effectively both independently and collaboratively in diverse and interdisciplinary teams.
Relates to: NoSQL Database Design and Analysis - Communicate effectively in a variety of modes, to expert and non-expert audiences, including in a professional context.
Relates to: NoSQL Database Design and Analysis
IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: NoSQL Database Design and Analysis, Examination (invigilated) - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: NoSQL Database Design and Analysis - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: NoSQL Database Design and Analysis - Communicate professionally and effectively in written, verbal and visual formats to a diverse range of stakeholders, considering the audience and explaining complex ideas in a simple and understandable manner in a range of IT-related contexts.
Relates to: NoSQL Database Design and Analysis