Big Data Systems
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This subject is available under ICMS undergraduate degrees, please click the button below to find an undergraduate course for you.
Subject Code:
DAT203A
Subject Type:
Specialisation
Credit Points:
3 credit points
Pre-requisite/Co-requisite:
DAT201A Applied Data Mining
Course level of study pre-requisite: a total of 12 credit points including ICT101A, ICT102A, ICT103A and DAT101A from level 100 core subjects prior to enrolling into level 200 core and specialisation subjects.
Subject Level:
200
Subject Rationale:
Due to the increasing importance of large and diverse volumes of data in today’s business world, organisations need systems and technologies to extract value from big data to enhance business decision making and remain competitive. Therefore, there is an increasing demand for data analytics graduates who can conceptualise, design, and implement big data systems.
The subject introduces big data and big data systems, their requirements and functionalities. It covers key areas such as databases and memory systems for big data, data privacy and security issues. As an essential enabler in managing big data systems, cloud computing will also be discussed along with the exploration of emerging trends and technologies in the big data systems domain.
The subject equips students with an understanding of how, when, and why these systems can be implemented and best used to solve specific business problems and create value within organisations.
Learning Outcomes:
a) Identify the unique properties and attributes of big data sets and the need for adopting big data systems within organisations.
b) Evaluate various big data database systems and their appropriateness in specific business scenarios.
c) Plan the application of various big data systems to manage big data sets.
d) Analyse key issues involved in the security and privacy of big data systems.
e) Examine emerging trends and technologies in the domain of big data systems.
Student Assessment:
| No | Assessment Task | Weighting | Learning Outcomes |
| 1 | Online Quiz (Invigilated) | 20% | a,b |
| 2 | Case Study | 35% | b, c |
| 3 | Big Data System Project (G) | ||
| Part A Business Report | 30% | b, c, d, e | |
| Part B Pitch | 15% |
Broad Topics to be Covered:
| Topic: |
Week 1: Introduction to Big Data
|
Week 2: Review of Big Data Systems
|
Week 3: Big Data Storage Systems
|
Week 4: NoSQL Systems
|
Week 5: Big Data Frameworks
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Week 6: Cloud Computing
|
Week 7: New SQL Systems
|
Week 8: Security for Big Data
|
Week 9: Privacy for Big Data
|
Week 10: Introduction to Common Big Data Platforms
|
Week 11: Future Trends in Big Data
|
Please note that these topics are often refined and subject to change so for up to date weekly topics and suggested reading resources, please refer to the Moodle subject page.