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Big Data and Analytics (Masters)
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ITECH5103 - Big Data and Analytics (Masters)
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20240200
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1.1
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2026-09-10
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2026-09-10
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Information Technology
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Institute of Innovation, Science & Sustainability
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Information Technology
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Postgraduate - Coursework
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15
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.125
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020303
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Database Management
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020303 - Database Management
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<a href="http://www.federation.edu.au/locate/unit/itech5103">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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9
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Masters Degree
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1
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<p>This unit provides fundamental concepts related to big data and analytics. This unit will explore the theory and applications of big data and demonstrate the process from data to decisions. Students will learn big data in various formats, data processing platforms and data analytics tools to transform, visualise, model, and communicate the insights hidden in the data, providing end users with timely knowledge to support decision making. The unit will explain the challenges organisations are facing with managing big data.</p>
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<p>Big data concepts, applications and tools;<br>
Structured data processing such as RDBMS, SQL<br>
Non-structured data processing<br>
Data analytics technologies<br>
Stream mining, real time analytics<br>
Predictive analytics<br>
Big data applications.</p>
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<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>
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Year
2027
Current Year
2026
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ITECH5103 - Big Data and Analytics (Masters)
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ITECH5103 - Big Data and Analytics (Masters)
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Semester 1
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Year
2027
2026
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Overview
Key information
Requisites
Learning outcomes
Assessment
FedTASK
Parent Region
Overview
Unit description
<p>This unit provides fundamental concepts related to big data and analytics. This unit will explore the theory and applications of big data and demonstrate the process from data to decisions. Students will learn big data in various formats, data processing platforms and data analytics tools to transform, visualise, model, and communicate the insights hidden in the data, providing end users with timely knowledge to support decision making. The unit will explain the challenges organisations are facing with managing big data.</p>
Unit content
<p>Big data concepts, applications and tools;<br> Structured data processing such as RDBMS, SQL<br> Non-structured data processing<br> Data analytics technologies<br> Stream mining, real time analytics<br> Predictive analytics<br> Big data applications.</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
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/itech5103">View unit fees</a>
Requisites
Prerequisite
None
Corequisite
None
Exclusion
<p>must not have completed 1 of "<a href="/ords/r/curriculum/catalogue/course?p6_code=GPSIT1103" target="_blank">GPSIT1103</a>" / "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH1103" target="_blank">ITECH1103</a>"</p>
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 the different types of data (e.g. structured, semi-structured, unstructured) and their sources (e.g. sensors, medical, business, social data)</p>
K2
<p>Discuss the stages of the big data analytics lifecycle.</p>
K3
<p>Outline the main tools and techniques in this area.</p>
K4
<p>Explain the importance of big data governance.</p>
S1
<p>Create and deliver reports using an analytical tool(s) on a real-world or simulated dataset.</p>
S2
<p>Research, explore and explain the current range of big data and analytics solutions and emerging trends and future issues.</p>
S3
<p>Explain contemporary IT industry practices/presentations relevant to Big Data and Analytics, and relate them to professional standards and your own career aspirations</p>
A1
<p>Communicate the stages, outcomes, and implications of the data analytics process, with reference to established academic literature.</p>
A2
<p>Apply big data analytics technology to a real-world or simulated dataset.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Students will create data analytics models such as ERD's and apply various data preparation and preprocessing methods to data, implemented as an SQL database.</p>
<p>Lab work and/or Assignment(s)</p>
<p>10%</p>
S1, A2
2
<p>Students will choose and/or implement an appropriate data analytic solution for a chosen specific problem and describe the components of the data analytics process. The assessment also includes theoretical questions drawing from the academic literature to provide context and opportunities for reflection on the analytical tasks undertaken, including consideration of big data, the different types of data and their sources.</p>
<p>Lab work and/or Assignment(s)</p>
<p>30%-50%</p>
K1, S1, A1, A2
3
<p>Students will create data analytics models, apply various data preparation, preprocessing, analytic solutions for a specific problem. This will be written up as a report, which also includes theoretical questions drawing from the academic literature to provide context and opportunities for reflection on the analytical tasks undertaken, including consideration of data governance.</p>
<p>Lab work and/or Assignment(s)</p>
<p>30%-50%</p>
K2, K3, K4, S1, S2, S3, A1, A2
4
<p>Tests and/or examinations covering a range of taught big data and analytics topics</p>
<p>Oral / Written Test(s)</p>
<p>0% - 30%</p>
K1, K2, K3, K4, S2, A1
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>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
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/itech5103">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: ITECH5103 - U1.1