Big Data Management
Duration
- One Semester or equivalent
Contact hours
- 36
On-campus unit delivery combines face-to-face and digital learning.
2022 teaching periods
| Hawthorn Higher Ed. Semester 2 |
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|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
| Swinburne Online Teaching Period 3 |
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Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
50 Credit Points from a Bachelor Degree.
Aims and objectives
This unit covers the management perspective of contemporary data management (particularly big data) issues in an organisational/ business context. Students will be introduced to issues that arise when data is gathered from multiple sources in various formats for many diverse purposes, as well as the relevant managerial, organisational, governance and Information Technology (IT) strategy issues. Students will explore why key aspects of a contemporary data management such as Master Data Management, Cloud storage, Social Media data, Data Warehouses, non-relational databases, Infrastructure as a Service, Platform as a Service and Software as a Service should not be regarded as exclusively techno-centric concepts but also as a business/management consideration.
4 Demonstrate critical thinking, problem solving, and ability to communicate effectively as a professional and function as an effective leader or member of a team
Students who successfully complete this unit will be able to:
1 Demonstrate an understanding of the complexity pertaining data, big data and data lifecycle, which may include data quality, data governance, acquisition & procurement, legal, ethical, risk and security issue
2 Analyse and evaluate appropriate data management solutions for specific business needs and requirements
3 Demonstrate an understanding of big data management as an enabler of business agility and innovation
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
Blended (for on-campus):
Scheduled hours: on-campus tutorials (8 x 1 hr), online tutorials (4x1 hr), on-campus lectures (8 x 2 hrs), online lectures (4 x 2 hrs)
Other Student workload: Students are expected to spend 4 hrs per week in engagement online with learning activities and discussion boards; and other activities including independent study and assessment tasks for a total of approximately 150 hours
Online:
Students are expected to spend 12 hours per week in engagement online with learning activities and discussion boards; and other activities including independent study and assessment tasks for a total of approximately 150 hours.
Assessment
Portfolio (Individual) 60-80 % OR (Group) 20-40%
comprising of:
- Assignments
- Reflective Practice Journal
- Executive Briefing Paper
General skills outcomes
During this unit students will receive feedback on the following key generic skills:
• problem solving skills
• communications skills
• ability to tackle unfamiliar problems
• ability to work independently, and
• ability to work in a group environment
Content
• Big Data, structured (records) vs unstructured (free-text) (may use open data, web crawler/scraping, SM feeds), Data Warehouse, Data Mart
• DB Storage, Cloud Storage, Master Data Management etc.
• Enterprise data life cycle, data governance
• Infrastructure and Architecture
• Data quality, relevance, data relationships (and/or relationships between datasets), value of data
• Cloud-based Data/Database service providers & models (i.e., IaaS)
• Sourcing & acquisitions of services, SLAs
• “Other issues”: legal, ethical, security
Study resources
- Reading materials.
Reading materials
Students are advised to check the unit outline in the relevant teaching period for appropriate textbooks and further reading