Big Data Management

Unit Outline (Higher Education)

Level of Unit in Course

AQF Level(s) of Course

Level of Unit in Course

Introductory

Intermediate

Effective Term:

2024/20

Institute / School :

Institute of Innovation, Science & Sustainability

Unit Title:

Big Data Management

Unit ID:

ITECH2302

Credit Points:

15.00

Prerequisite(s):

(ITECH1103)

Co-requisite(s):

Nil

Exclusion(s):

Nil

ASCED:

020303

Other Change:

Brief description of the Unit

This unit introduces students to the core concepts, theories and technologies involved in managing big data. Focusing on computing models, architectures, approaches and software to manage big data, students will develop their understanding of practical applications and challenges by managing and analysing big data in a distributed and/or parallel fashion. Students will be introduced to the use of big data management framework Hadoop, big data storage techniques, distributed and parallel computing, Map-Reduce and big data management and analytic approaches. Students will have the opportunity to engage in areas of study including big data stream processing, big data management with data mining and visual analysis for managing big data.

Grade Scheme:

Graded (HD, D, C, P, MF, F, XF)

Work Experience Indicator:

No work experience

Placement Component: No

Supplementary Assessment:

Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment

Course Level:

Learning Outcomes:

Knowledge:

K1.	Describe defining characteristics, categories, examples and challenges of big data.

K2.	Illustrate key storage data, data types and documents for big data management.

K3.	Explain basic theories and techniques that underpin big data management such as management issues, strategies, interface models, infrastructures and related frameworks.

Skills:

S1.	Demonstrate skills in managing data using related analytical tools.

S2.	Manage data using analytical tools.

S3.	Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.

Application of knowledge and skills:

A1.	Plan effective big data storage and processing for specific business applications.

A2.	Use appropriate tools to analyse, process and visualize data for big data management and analytics.

A3.	Present big data management scenarios using oral and written communication skills and include ethical considerations.

Unit Content:

This unit will cover big data management framework, Hadoop, big data storage techniques, distributed and parallel computing, Map-Reduce and big data management and analytic approaches.

Topics may include:
1. Instruction to big data management and applications.
2. Data representation & abstraction for big data management.
3. Business Intelligence: OLAP, Data Warehouse
4. Big data storage management.
5. Big data analysis techniques.
6. Distributed and parallel computing using Map-Reduce.
7. Hadoop ecosystem.
8. Big data stream processing
9. Visual analysis for managing big data
10. Case study.

Graduate Attributes:

Federation University recognises that students require key transferable employability skills to prepare them for their future workplace and society. FEDTASKS (Transferable Attributes Skills and Knowledge) provide a targeted focus on five key transferable Attributes, Skills, and Knowledge that are be embedded within curriculum, developed gradually towards successful measures and interlinked with cross-discipline and Co-operative Learning opportunities. One or more FEDTASK, transferable Attributes, Skills or Knowledge must be evident in the specified learning outcomes and assessment for each FedUni Unit, and all must be directly assessed in each Course.

FED TASK and descriptor		Development and acquisition of FEDTASKS in the Unit
FED TASK and descriptor		Learning outcomes (KSA)	Assessment task (AT#)
FEDTASK 1 Interpersonal	Students will demonstrate the ability to effectively communicate, inter-act and work with others both individually and in groups. Students will be required to display skills in-person and/or online in: • Using effective verbal and non-verbal communication • Listening for meaning and influencing via active listening • Showing empathy for others • Negotiating and demonstrating conflict resolution skills • Working respectfully in cross-cultural and diverse teams.	K1, K2, S1	AT1
FEDTASK 2 Leadership	Students will demonstrate the ability to apply professional skills and behaviours in leading others. Students will be required to display skills in: • Creating a collegial environment • Showing self -awareness and the ability to self-reflect • Inspiring and convincing others • Making informed decisions • Displaying initiative	S1, S2, S3, A3	AT2
FEDTASK 3 Critical Thinking and Creativity	Students will demonstrate an ability to work in complexity and ambiguity using the imagination to create new ideas. Students will be required to display skills in: • Reflecting critically • Evaluating ideas, concepts and information • Considering alternative perspectives to refine ideas • Challenging conventional thinking to clarify concepts • Forming creative solutions in problem solving.	K3, A1	AT3
FEDTASK 4 Digital Literacy	Students will demonstrate the ability to work fluently across a range of tools, platforms and applications to achieve a range of tasks. Students will be required to display skills in: • Finding, evaluating, managing, curating, organising and sharing digital information • Collating, managing, accessing and using digital data securely • Receiving and responding to messages in a range of digital media • Contributing actively to digital teams and working groups • Participating in and benefiting from digital learning opportunities.	S1,S2, S3, A3	AT1, AT2
FEDTASK 5 Sustainable and Ethical Mindset	Students will demonstrate the ability to consider and assess the consequences and impact of ideas and actions in enacting ethical and sustainable decisions. Students will be required to display skills in: • Making informed judgments that consider the impact of devising solutions in global economic environmental and societal contexts • Committing to social responsibility as a professional and a citizen • Evaluating ethical, socially responsible and/or sustainable challenges and generating and articulating responses • Embracing lifelong, life-wide and life-deep learning to be open to diverse others • Implementing required actions to foster sustainability in their professional and personal life.	K3, A1	AT3

Learning Task and Assessment:

This unit introduces students to the core concept, theory and technologies involved in managing big data. Students will have the opportunity to engage in the unit study through lectures, lab projects and other learning activities. Students are encouraged to understand the unit description, including the requirement of assessment tasks before taking the unit.

	Learning Outcomes Assessed	Assessment Tasks	Assessment Type	Weighting
1.	S1, K1, K2	Install software, build a working environment of big data management and explain related basic concept.	Assignment(s)	10%-20%
2.	S1, S2, S3, A3	Students implement lab projects by using related software tools and report their lab work.	Assignment(s)	20%-30%
3.	K3, A1, A4	Students will demonstrate a range of skills in a simulated workplace project, including managing big data, oral and written presentations and ethical considerations.	Presentation and Reflection	20 - 30%
4.	K1, K2,K3, S2, S3, A1	Examinations/test will cover topics taught in the unit.	Examination/test	30%-40%

Adopted Reference Style:

APA

Professional Standards / Competencies:

Standard / Competency

Australian Computer Society - Core Body of Knowledge: 2003 accreditation

Attribute			Assessed	Level
1 ICT Problem Solving (PS)
	1.1 Modelling methods and processes.
		1.1.1 Understand problems, handle abstraction and design solutions.	Yes	Intermediate
2 Professional Knowledge (PK)
	2.1 Ethics
		2.1.1 Fundamental ethical notions (virtues, duty, responsibility, harm, benefit, rights, respect and consequences);	No	Intermediate
	2.3 Teamwork concepts and issues
		2.3.1 Collaboration, group dynamics, leadership styles, conflict resolution, team development and groupware	No	Intermediate
	2.4 Communication
		2.4.1 Oral and written presentations, technical report writing, writing user documentation and the development of effective interpersonal skills	Yes	Intermediate
	2.6 History and status of discipline
		2.6.1 Where and when their discipline began and how it has evolved, in addition to understanding of ongoing issues in the discipline	Yes	Intermediate
3 Technology Building (TB)
	3.3 Systems development
		3.3.1 An understanding is required of how to develop or acquire software (information) systems that satisfy the requirements of users and customers.	No	Intermediate
		3.3.3 There should also be knowledge of methodologies and processes for developing systems	No	Intermediate
4 Technology Resources (TR)
	4.2 Data and information management
		4.2.1 Data modelling and abstraction	No	Intermediate
		4.2.2 Physical file storage techniques	No	Intermediate
		4.2.3 Database Management Systems (DBMS)	No	Intermediate
		4.2.4 Information assurance and security in a shared environment	No	Advanced
6 Outcomes Management (OM)
	6.1 ICT Governance
		6.1.2 ICT specific governance issues, including ICT management and ICT value assessment	No	Intermediate
		6.1.4 Security policy	No	Intermediate

Skills Framework for the Information Age (SFIA): Initial

Attribute			Assessed	Level
1 Strategy and architecture
	1.1 Information strategy
		1.1.2 Information management	Yes	2
		1.1.6 Information analysis	Yes	2
	1.2 Advice and guidance
		1.2.1 Consultancy	Yes	2
		1.2.2 Technical specialism	Yes	2
	1.3 Business strategy and planning
		1.3.1 Research	No	2
	1.4 Technical strategy and planning
		1.4.7 Data management	No	3
		1.4.8 Methods and tools	No	2
2 Business change
	2.1 Business change implementation
		2.1.3 Project management	No	2
3 Solution development and implementation
	3.1 Systems development
		3.1.2 Data analysis	Yes	2
		3.1.5 Database / repository design	Yes	3
4 Service management
	4.4 Service operation
		4.4.1 System software	No	1
		4.4.7 Storage management	Yes	3
		4.4.9 Problem management	Yes	1
5 Procurement and management support
	5.2 Quality and conformance
		5.2.2 Quality assurance	Yes	2

Australian Computer Society - Core Body of Knowledge: 2016 accreditation

Attribute			Assessed	Level
Essential Core ICT Knowledge
	ICT Professional Knowledge
		Ethics	No	Comprehension
		Teamwork concepts & issues	No	Application
		Interpersonal communications	No	Application
	ICT Problem Solving
		Abstraction	No	Comprehension
		Design	No	Comprehension
General ICT Knowledge
	Technology Resources
		Data & information management	Yes	Knowledge
	Technology Building
		Systems Development	No	Analysis
		Systems Acquisition	No	Analysis
	ICT Management
		IT Governance & organisational issues	No	Analysis
		Security Management	No	Comprehension

Australian Computer Society - Core Body of Knowledge: 2023 accreditation

Attribute			Assessed	Level
Core ICT Knowledge
	ICT Fundamentals
		Computational thinking: situation analysis and modelling using a range of methods and patterns to frame it so a computer system could operate effectively within it	Yes	Intermediate
		Design thinking: methods and tools that are used for handling abstraction could vary a great deal with the branch of ICT, from circuit diagrams to data modelling tools to business process modelling	Yes	Intermediate
	Information & Data Science and Engineering
		Nature of data, information and knowledge, meta-data, abstraction and representational quality	Yes	Intermediate
		Database Management Systems and SQL, non-relational systems (blockchain, NoSQL, files)	Yes	Intermediate
		Data Science and Engineering, data analytics, mining and visualisation, big data	Yes	Intermediate
	Computational Science and Engineering
		Process and algorithm modelling: methods of algorithm design, software quality	Yes	Intermediate
	Application Systems
		Types of application: organisational operations (transaction processing, executive information systems), simulation and decision support, information management (digital document (text, video, sound, image) creation, storage, communication and information retrieval), knowledge management, digital platforms and markets	Yes	Intermediate
Professionalism as it applied in ICT
	Professional ICT Ethics
		ICT specific ethics issues: adverse stakeholder impacts of ICT, surveillance and privacy, data matching, autonomous computing, digital divide, etc.	No	Intermediate
	Professional Communication
		Communication with different audiences (technical, managerial, users and non-digitally orientated audiences) in different forums (meetings, presentations, networking)	Yes	Intermediate
		Forms and styles of documentation - technical reports and specifications, progress reports	Yes	Intermediate

Skills Framework for the Information Age (SFIA): Version 8

Attribute			Assessed	Level
Strategy and architecture
	Strategy and planning
		RSCH Research (Levels 2 - 6) Systematically creating new knowledge by data gathering, innovation, experimentation, evaluation and dissemination.	Yes	3
	Advice and guidance
		CNSL Consultancy (Levels 4 - 7) Providing advice and recommendations, based on expertise and experience, to address client needs.	Yes	3
Development and implementation
	Data and analytics
		DATM Data management (Levels 4 - 6) Developing and implementing plans, policies, and practices that control, protect and optimise the value of data assets.	Yes	3
		DATS Data science (Levels 2 - 7) Applying mathematics, statistics, data mining and predictive modelling techniques to gain insights, predict behaviours and generate value from data.	Yes	4
		MLNG Machine learning (Levels 2 - 6) Developing systems that learn through experience and by the use of data.	Yes	3
		BINT Business intelligence (Levels 2 - 5) Developing, producing and delivering regular and one-off management information to provide insights and aid decision-making.	Yes	3
		VISL Data visualisation (Levels 3 - 5) Facilitating understanding of data by displaying concepts, ideas, and facts using graphical representations.	Yes	3