BIG DATA MANAGEMENT ON THE CLOUD

CSE4BDC

2017

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 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites CSE2DBF OR CSE4DBF and CSE1IOO OR CSE4IOO

Co-requisitesN/A

Incompatible subjects CSE3BDC

Equivalent subjectsN/A

Special conditionsN/A

Graduate capabilities & intended learning outcomes

01. Understand the benefits of 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:
Critical Thinking (Critical Thinking)
Discipline-specific GCs (Discipline-specific GCs)
Inquiry/ Research (Inquiry/ Research)

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:
Inquiry/ Research (Inquiry/ Research)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)
Critical Thinking (Critical Thinking)

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:
Creative Problem-solving (Creative Problem-solving)
Inquiry/ Research (Inquiry/ Research)
Critical Thinking (Critical Thinking)
Discipline-specific GCs (Discipline-specific GCs)

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:
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)

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 (Discipline-specific GCs)

06. Identify advantages and disadvantages of state-of-the-art technologies developed by research projects in the area of big data analytics using cloud-based services.

Activities:
Lectures in weeks 10 to 12 on advanced techniques for big data analytics. The students will pratice this via practice questions during lectures and take home study questions.
Related graduate capabilities and elements:
Critical Thinking (Critical Thinking)
Inquiry/ Research (Inquiry/ Research)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)

Subject options

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Start date between: and    Key dates

Melbourne, 2017, Semester 1, Day

Overview

Online enrolmentNo

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*
10 Laboratories (2 hours each)10 03, 04, 05
One 3-hour examination60 01, 02, 03, 04, 06
Programming Assignment (equivalent to 1250 words)30 03
The students are required to achieve greater than 50% for the non-exam components as a hurdle