BIG DATA MANAGEMENT ON THE CLOUD

CSE3BDC

2018

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.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorZhen He

Available to Study Abroad StudentsYes

Subject year levelYear Level 3 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites CSE2DBF, CSE1OOF

Co-requisitesN/A

Incompatible subjects CSE4BDC

Equivalent subjectsN/A

Special conditionsN/A

Graduate capabilities & intended learning outcomes

01. Identify the benefits of using cloud computing over traditional methods for managing big data.

Activities:
Lectures on the architecture of cloud-based systems in weeks 1 and 2. The students will practice this by answering questions during lectures and answering study questions.
Related graduate capabilities and elements:
Inquiry/ Research
Critical Thinking
Discipline-specific GCs

02. Identify the best type of cloud-based service to use for a particular application scenario.

Activities:
Lectures in week 2 and 3 on the three types of cloud-based services including: infrastructure as a service, platform as a service and software as a service. The students will practice this by answering questions during lectures and answering study questions.
Related graduate capabilities and elements:
Discipline-specific GCs
Critical Thinking
Creative Problem-solving
Inquiry/ Research

03. Write efficient map and reduce programs to analyze large data sets.

Activities:
The students will pratice answering questions during lectures in week 4 and 5. The students will practice programming map and reduce in the labs and during the programming assignment.
Related graduate capabilities and elements:
Inquiry/ Research
Creative Problem-solving
Discipline-specific GCs
Critical Thinking

04. Write efficient programs that query cloud-hosted database systems.

Activities:
The students will practice answering questions during lectures in week 6. The students will practice writing cloud-hosted database queries in the labs and during the programming assignment.
Related graduate capabilities and elements:
Discipline-specific GCs
Creative Problem-solving

05. Setup cloud-hosted database systems.

Activities:
Students will practice setting up cloud-based database systems during the labs.
Related graduate capabilities and elements:
Discipline-specific GCs

Subject options

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Start date between: and    Key dates

Dandenong, 2018, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorZhen He

Class requirements

Laboratory Class Week: 10 - 22
One 2.0 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% 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.10 03, 04, 05
One 3-hour examination70 01, 02, 03, 04
Programming Assignment (equivalent to 1000 words)Students are required to achieve greater than 50% for the non-exam components as a hurdle)20 03

Melbourne, 2018, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorZhen He

Class requirements

Laboratory Class Week: 11 - 22
One 2.0 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% 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.10 03, 04, 05
One 3-hour examination70 01, 02, 03, 04
Programming Assignment (equivalent to 1000 words)Students are required to achieve greater than 50% for the non-exam components as a hurdle)20 03