Skip to Main Content
Catalogue Link
<a href="/ords/r/curriculum/catalogue/home" class="t-Header-logo-link"><span class="apex-logo-text">Handbook</span></a>
Hidden Page Items
New
5
New
HE Unit Template
New
Big Data Management
New
ITECH2302 - Big Data Management
New
20250600
New
New
New
New
Course
New
Unit
New
New
3.3
New
New
2026-09-10
New
2026-09-10
New
Information Technology
New
New
New
New
Institute of Innovation, Science & Sustainability
New
Information Technology
New
Undergraduate
New
15
New
New
.125
New
020303
New
Database Management
New
020303 - Database Management
New
<a href="http://www.federation.edu.au/locate/unit/itech2302">View unit fees</a>
New
Graded (e.g. HD, D, C, etc)
New
7
New
Bachelor Degree
New
Intermediate
New
New
New
New
1
New
New
New
New
New
false
New
New
New
<p>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.</p>
New
New
<p>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.<br><br>
Topics may include:<br>
1. Instruction to big data management and applications.<br>
2. Data representation & abstraction for big data management.<br>
3. Business Intelligence: OLAP, Data Warehouse<br>
4. Big data storage management.<br>
5. Big data analysis techniques.<br>
6. Distributed and parallel computing using Map-Reduce.<br>
7. Hadoop ecosystem.<br>
8. Big data stream processing<br>
9. Visual analysis for managing big data<br>
10. Case study.</p>
New
true
New
<p>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.</p>
New
true
Hidden Page Items
Semester
Semester
0200
Year
Year
2027
Current Year
2026
Breadcrumb Positioning
Handbook
ITECH2302 - Big Data Management
Pseudo Breadcrumb
ITECH2302 - Big Data Management
Breadcrumb Type
Unit
Catalogue Term and Year
Version Text
You are viewing a version for
Semester
Semester 1
Semester 2
Summer Semester
Year
2027
2026
Download PDF
RDS Holder
Overview
Key information
Requisites
Learning outcomes
Assessment
FedTASK
Parent Region
Overview
Unit description
<p>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.</p>
Unit content
<p>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.<br><br> Topics may include:<br> 1. Instruction to big data management and applications.<br> 2. Data representation & abstraction for big data management.<br> 3. Business Intelligence: OLAP, Data Warehouse<br> 4. Big data storage management.<br> 5. Big data analysis techniques.<br> 6. Distributed and parallel computing using Map-Reduce.<br> 7. Hadoop ecosystem.<br> 8. Big data stream processing<br> 9. Visual analysis for managing big data<br> 10. Case study.</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
020303 - Database Management
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/itech2302">View unit fees</a>
Requisites
Prerequisite
<p> must have completed <a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH1103" target="_blank">ITECH1103</a></p>
Corequisite
None
Exclusion
None
Learning outcomes
Learning outcomes
<p>On successful completion of this unit, students are expected to gain the following [K]nowledge, [S]kills and [A]pplication of knowledge & skills</p>
Learning Outcomes
Ref
Outcome
K1
<p>Describe defining characteristics, categories, examples and challenges of big data.</p>
K2
<p>Illustrate key storage data, data types and documents for big data management.</p>
K3
<p>Explain basic theories and techniques that underpin big data management such as management issues, strategies, interface models, infrastructures and related frameworks.</p>
S1
<p>Demonstrate skills in managing data using related analytical tools.</p>
S2
<p>Manage data using analytical tools.</p>
S3
<p>Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.</p>
A1
<p>Plan effective big data storage and processing for specific business applications.</p>
A2
<p>Use appropriate tools to analyse, process and visualize data for big data management and analytics.</p>
A3
<p>Present big data management scenarios using oral and written communication skills and include ethical considerations.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Install software, build a working environment of big data management and explain related basic concept.</p>
<p>Assignment(s)</p>
<p>10%-20%</p>
K1, K2, S2
2
<p>Students implement lab projects by using related software tools and report their lab work.</p>
<p>Assignment(s)</p>
<p>20%-40%</p>
S1, S2, S3, A2
3
<p>Students will demonstrate a range of skills in a simulated workplace project, including managing big data, oral and written presentations and ethical considerations.</p>
<p>Presentation and Reflection</p>
<p>20 - 60%</p>
K1, K2, K3, A1, A3
Supplementary assessment available:
Yes
Supplementary assessment information:
<p>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.</p>
FedTASK
FedTASK
<p>Federation University recognises that students require key transferable employability skills to prepare them for their future workplace and society. FedTASKs (<strong>T</strong>ransferable <strong>A</strong>ttributes <strong>S</strong>kills and <strong>K</strong>nowledge) provide a targeted focus on five key, transferable Attributes, Skills, and Knowledge that are embedded within curriculum, developed gradually towards successful measures and interlinked with cross-discipline and co-operative learning opportunities.</p>
FedTASK
Description of FedTASK outcome
Level
FedTASK 1: Interpersonal
The ability to effectively communicate, interact and work with others both individually and in groups.
FedTASK 2: Leadership
The ability to apply professional skills and behaviours in leading others.
FedTASK 3: Critical Thinking and Creativity
The ability to work in complexity and ambiguity using imagination to create new ideas.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 4: Digital Literacy
The ability to work fluently across a range of tools and applications to achieve a range of skills.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 5: Sustainable and Ethical Mindset
The ability to consider and assess the consequences and impact of ideas and actions in enacting ethical and sustainable decisions.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
020303 - Database Management
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/itech2302">View unit fees</a>
Additional information
Cards Section - Non Research
Add Info Static Text
Internal reference: ITECH2302 - U3.3