41091 Data Systems
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 48024 Programming 2 OR 41082 Introduction to Data Engineering
Description
This subject introduces the concepts of systems engineering for complex, data-centric systems. It explores the lifecycle of data-centric systems from initial design through to system development, then production and ongoing management. Students learn about Extract, Transform, Load processes for building data pipelines, using Python for data engineering and reporting, the Hadoop ecosystem and cloud infrastructure providers of data systems. The subject is project based. Students do a combination of workshops on data engineering topics and project work as a team.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Define requirements and specifications of data system. (B.1) |
|---|---|
| 2. | Demonstrate a systematic design and thinking process for data system development. (C.1) |
| 3. | Prototype or implement data system according to system specifications. (D.1) |
| 4. | Communicate effectively to data system project stakeholders. (E.1) |
| 5. | Work effectively in a team to develop a data system, demonstrating continuous improvement and independence. (E.1, F.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Socially Responsible: FEIT graduates identify, engage, interpret and analyse stakeholder needs and cultural perspectives, establish priorities and goals, and identify constraints, uncertainties and risks (social, ethical, cultural, legislative, environmental, economics etc.) to define the system requirements. (B.1)
- Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
- Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
- Reflective: FEIT graduates critically self-review their performance to improve themselves, their teams, and the broader community and society. (F.1)
Contribution to the development of graduate attributes
Engineers Australia Stage 1 Competencies
This subject contributes to the development of the following Engineers Australia Stage 1 Competencies:
- 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 1.5. Knowledge of engineering design practice and contextual factors impacting the engineering discipline.
- 2.1. Application of established engineering methods to complex engineering problem solving.
- 2.2. Fluent application of engineering techniques, tools and resources.
- 2.3. Application of systematic engineering synthesis and design processes.
- 2.4. Application of systematic approaches to the conduct and management of engineering projects.
- 3.2. Effective oral and written communication in professional and lay domains.
- 3.5. Orderly management of self, and professional conduct.
- 3.6. Effective team membership and team leadership.
Teaching and learning strategies
The subject is carried out through the development of data systems in collaborative classes.
The collaborative classes are designed to support and guide the students through the development life cycle in data system project. The class is composed of workshop session and project development session. In the workshop session, theories and concepts of data system development will be discussed. In the project development session, students will participate in team work to develop a data system.
At the beginning of the semester, each student will join a team. Each team will choose a data system project. This project will be carried out through the development phases of planning, requirements and specification, design, implementation and testing. The students will present their project work in the class. Other teams are required to review and critique other team’s presentations.
Content (topics)
- Data system architecture design and lifecycle
- Extract, Transform, Load design and implementation
- Python for data engineering
- Hadoop ecosystem
- Cloud data infrastructure providers, e.g. Amazon AWS
- Reporting
Assessment
Assessment task 1: Data system requirements and design specifications
| Intent: | Negotiate the scope and outcomes of the project with the subject staff. Apply design methodology in data system development. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1, E.1 and F.1 |
| Type: | Report |
| Groupwork: | Group, group and individually assessed |
| Weight: | 30% |
Assessment task 2: Data system implementation
| Intent: | Complete the system implementation based on the design documents. Testing the final system using user requirements. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1, E.1 and F.1 |
| Type: | Project |
| Groupwork: | Group, group and individually assessed |
| Weight: | 60% |
Assessment task 3: Individual logbook
| Intent: | Encourage students' continuous participation in the subject’s activities, concepts and theory. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1, D.1, E.1 and F.1 |
| Type: | Journal |
| Groupwork: | Individual |
| Weight: | 10% |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.