Big Data
Overview
This unit enables students to understand the nature of Big Data, and to evaluate and apply solutions to the problems of storing, integrating and analysing heterogeneous data sets with varying degrees of structure from diverse sources using the appropriate tools in order to extract meaningful information.
Requisites
Rule
COS20015 Fundamentals of Data Management
OR
INF10002 Database Analysis and Design
OR
INF10025 Data Management and Analytics
AND
COS10009 Introduction to Programming
OR
Entry to MA-ITPC1
OR
COS60009 Data Management for the Big Data Age
OR
INF60009 Database, Analysis and Design
AND
COS60006 Introduction to Programming
OR
TNE60003 Introduction to Network Programming
OR
COS60010 Technology Inquiry Project
27-October-2024
02-November-2025
Learning outcomes
Students who successfully complete this unit will be able to:
- Discuss the challenges and opportunities of Big Data in the context of its potential for organisations.
- Propose efficient solutions for the storage and management of large data sets
- Use efficient tools to query diverse forms of data storage, such as NoSQL data sources
- Compare and apply technologies and algorithms to extract and integrate information from data sets with varying degrees of structure
- Appraise the quality and fitness for purpose of the information extracted, using suitable statistical methods
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Live Online Lecture | 1.00 | 12 weeks | 12 |
| On-campus Class | 2.00 | 12 weeks | 24 |
| Unspecified Activities Independent Learning | 9.50 | 12 weeks | 114 |
| TOTAL | 150 |
Sydney
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| On-campus Lecture | 2.00 | 12 weeks | 24 |
| On-campus Class | 2.00 | 12 weeks | 24 |
| Unspecified Activities Independent Learning | 8.50 | 12 weeks | 102 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Portfolio | Individual/Group | 100% | 1,2,3,4,5 |
Content
- Big Data, its nature, challenges and opportunities
- Storage and management technologies
- Query tools
- Tools and techniques for extraction of information from structured and unstructured data
- Integration of data/information from diverse sources
- Statistical methods for information extraction and quality evaluation
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.