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HE Unit Template
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Big Data Analytics
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GPSIT1103 - Big Data Analytics
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20260200
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2.3
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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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Undergraduate
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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/gpsit1103">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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5
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Diploma, Undergraduate Certificate
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Introductory
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<p>This unit provides fundamental concepts related to big data and analytics and will explore the theory and applications of big data and demonstrate the process from data to decisions. Students will examine the complete process from data to decision-making, learning to work with big data in various formats, data processing platforms, and analytics tools. They will develop skills to transform, visualise, model, and communicate insights hidden within data; providing end users with timely, actionable knowledge to support informed decisions. This unit will explain the challenges organisations are facing in managing big data. To support student success, additional learning hours are provided to support the development of students’ academic and study skills.</p>
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<p>Topics may include:</p>
<p>1. Different types of data (e.g. structured, semi-structured, unstructured)</p>
<p>2. Sources of data (e.g. sensors, medical, business, social data)</p>
<p>3. Database life cycle (e.g., requirements analysis, design, implementation, maintenance)</p>
<p>4. Database design principles: normalisation, entity-relationship modelling.</p>
<p>5. Relational database concepts: tables, rows, columns, keys, relationships.</p>
<p>6. SQL (Structured Query Language): basic queries, data manipulation, data definition, joins.</p>
<p>7. Definition, scope and components of Information Systems.</p>
<p>8. Representation and use of data in Information System (Master Data, Transactional Data)</p>
<p>9. Components of an Information System (e.g., hardware, software, data, procedures, and people)</p>
<p>10. Types of Information Systems: transaction processing systems, management information systems, decision support systems, executive support systems, etc.</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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2027
Current Year
2026
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GPSIT1103 - Big Data Analytics
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GPSIT1103 - Big Data Analytics
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Semester 1
Semester 2
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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 and will explore the theory and applications of big data and demonstrate the process from data to decisions. Students will examine the complete process from data to decision-making, learning to work with big data in various formats, data processing platforms, and analytics tools. They will develop skills to transform, visualise, model, and communicate insights hidden within data; providing end users with timely, actionable knowledge to support informed decisions. This unit will explain the challenges organisations are facing in managing big data. To support student success, additional learning hours are provided to support the development of students’ academic and study skills.</p>
Unit content
<p>Topics may include:</p> <p>1. Different types of data (e.g. structured, semi-structured, unstructured)</p> <p>2. Sources of data (e.g. sensors, medical, business, social data)</p> <p>3. Database life cycle (e.g., requirements analysis, design, implementation, maintenance)</p> <p>4. Database design principles: normalisation, entity-relationship modelling.</p> <p>5. Relational database concepts: tables, rows, columns, keys, relationships.</p> <p>6. SQL (Structured Query Language): basic queries, data manipulation, data definition, joins.</p> <p>7. Definition, scope and components of Information Systems.</p> <p>8. Representation and use of data in Information System (Master Data, Transactional Data)</p> <p>9. Components of an Information System (e.g., hardware, software, data, procedures, and people)</p> <p>10. Types of Information Systems: transaction processing systems, management information systems, decision support systems, executive support systems, etc.</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/gpsit1103">View unit fees</a>
Requisites
Prerequisite
None
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 the stages involved in designing and implementing modern data solutions, including relational and big data systems.</p>
K2
<p>Identify and classify different types of data (e.g. structured, semi-structured, unstructured) and their sources.</p>
K3
<p>Outline common data analytics techniques, tools, and applications.</p>
K4
<p>Recognise the key stages of the data analytics lifecycle and the challenges organisations face in managing data.</p>
S1
<p>Apply basic techniques to design and build a data-centric application.</p>
S2
<p>Use analytical tools to explore and interpret real-world datasets.</p>
S3
<p>Identify current trends and challenges in big data and analytics.</p>
S4
<p>Develop the appropriate English language and academic skills to successfully study at an undergraduate level.</p>
A1
<p>Communicate the outcomes of a data analytics process in a clear and structured manner.</p>
A2
<p>Apply basic big data analytics tools to a real-world dataset.</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>Students will describe different types of data and their sources, demonstrating foundational understanding of data classification and origin.</p>
<p>Tutorial task(s)</p>
<p>10-30%</p>
K1, K2, K3, K4, S1, S2, S3, S4, A2
2
<p>Students will select and/or implement an appropriate data management solution for a specific problem. They will describe the components of the solution and respond to theoretical questions that provide context and encourage reflection on the analytical tasks undertaken.</p>
<p>Practical Assignment(s)</p>
<p>30 - 60%</p>
K2, S1, S2, S4, A1, A2
3
<p>Students will select an appropriate information systems solution for a specific problem and describe its components. The task includes theoretical questions to support contextual understanding and reflection on the analytical process.</p>
<p>Oral Presentation(s)</p>
<p>30-60%</p>
K1, K2, K3, K4, S1, S3, S4, 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
Description of FedTASK outcome
Level
FedTASK 1: Interpersonal
The ability to effectively communicate, interact and work with others both individually and in groups.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 2: Leadership
The ability to apply professional skills and behaviours in leading others.
<p>Level 1 - Students require directions and boundaries from mentor</p>
FedTASK 3: Critical Thinking and Creativity
The ability to work in complexity and ambiguity using imagination to create new ideas.
<p> </p><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 1 - Students require directions and boundaries from mentor</p>
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:
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/gpsit1103">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: GPSIT1103 - U2.3