BIG DATA MANAGEMENT ON THE CLOUD
CSE3BDC
2020
Credit points: 15
Subject outline
Companies are acquiring massive amounts of data and also providing internet based service to millions of people. This is extremely challenging due to the large scale of data involved and the huge number of concurrent requests by users. In this subject we will study the current state-of-the-art technologies for analysing huge amounts of data and responding to millions of user requests within one second. Currently the most cost efficient way of achieving the above aim is to use large-scale cloud-based services offered by vendors such as Amazon, Google, IBM, Microsoft, etc. We will study how to use the cloud services provided by these vendors to meet the big data needs of businesses. In particular this subject will include the following topics: cloud architectures, parallel database systems, map and reduce, key value stores, transaction support in the cloud, virtualization, and multi-tenant database systems.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Zhen He
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 3 - UG
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: CSE1OOF AND CSE2DBF
Co-requisites: N/A
Incompatible subjects: CSE4BDC
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Zhen He
Class requirements
Laboratory ClassWeek: 11 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
Laboratory work (equivalent to 500 words)Each lab will include programming tasks which students need to complete. The completed tasks will be marked by the lab demonstrator based on correctness. | N/A | N/A | No | 10 | SILO3, SILO4, SILO5 |
One 3-hour examination | N/A | N/A | No | 70 | SILO1, SILO2, SILO3, SILO4 |
Programming Assignment (equivalent to 1000 words)Students are required to achieve greater than 50% for the non-exam components as a hurdle) | N/A | N/A | Yes | 20 | SILO3 |
Dandenong (Chisholm Institute), 2020, Semester 1, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Zhen He
Class requirements
Laboratory ClassWeek: 10 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
Laboratory work (equivalent to 500 words)Each lab will include programming tasks which students need to complete. The completed tasks will be marked by the lab demonstrator based on correctness. | N/A | N/A | No | 10 | SILO3, SILO4, SILO5 |
One 3-hour examination | N/A | N/A | No | 70 | SILO1, SILO2, SILO3, SILO4 |
Programming Assignment (equivalent to 1000 words)Students are required to achieve greater than 50% for the non-exam components as a hurdle) | N/A | N/A | Yes | 20 | SILO3 |