Big Data Management
Overview
This unit examines contemporary data management from a managerial perspective, addressing the challenges of handling diverse and large-scale data in organisational contexts. Students will explore data governance, ethics, data quality, and lifecycle management, alongside cloud computing models and sourcing strategies. Emphasis is placed on leveraging business intelligence and analytics to derive data-driven insights and foresights. Key technologies, such as data warehouses, data lakes, Master Data Management, and emerging solutions such as Artificial Intelligence and Machine Learning, are considered not only as technical tools but as strategic enablers of innovation, agility, and responsible decision-making in the era of big data.
Requisites
02-November-2025
08-February-2026
31-May-2026
01-November-2026
07-February-2027
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Describe key concepts in contemporary data management, including big data, data quality, data governance, ethics, and cloud computing models in generating data-driven insights and supporting organisational decision-making
- Identify how technologies such as data warehouses, data lakes, AI, and machine learning contribute to business data strategies
- Apply data analysis and visualisation techniques to interpret and communicate insights using enterprise analytics tools
- Communicate effectively and professionally as either a leader or a member of a team in technology-driven projects
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| On-campus Class |
2.00 | 12 weeks | 24 |
| Online Lecture (asynchronous) |
1.00 | 12 weeks | 12 |
| Unspecified Activities Independent Learning |
9.50 | 12 weeks | 114 |
| TOTAL | 150 |
Swinburne Online
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Online Directed Online Learning and Independent Learning | 12.50 | 12 weeks | 150 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Case Study | Group | 30-50% | 1,3,4 |
| Assessment | Individual | 30-50% | 3 |
| Portfolio | Group | 20-40% | 1,2,3 |
Content
- Contemporary issues in Data management
- Big Data, structured (records) vs unstructured (free-text), Data Warehouse, Data Mart, Data Lake
- DB Storage, Cloud Storage, Master Data Management.
- Enterprise data life cycle, data governance
- Infrastructure and Architecture
- Data quality, relevance, data relationships, value of data
- Cloud-based Data/Database service providers & models (i.e., IaaS, PaaS)
- Data Ethics, ethical considerations pertaining data, Information Security
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.