Type: | Undergraduate Subject |
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Code: | DTSC13-300 |
EFTSL: | 0.125 |
Faculty: | Bond Business School |
Semesters offered: |
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Credit: | 10 |
Study areas: |
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Subject fees: |
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Description
Using an information systems approach, this subject outlines the design principles and techniques necessary to produce appropriate infrastructure specifications for different data analytic systems. These requirements can be specified in terms of people, procedures, data, software, and hardware. Successful designs will allow systems to automatically extract insights from vast amounts of available data. Topics include, but are not limited to, key modern issues such as job roles in data analytic ecosystems, the operation of organisations, security and data integrity principles, business processes, blockchains, NoSQL databases, cloud solutions, software options and fundamental tenets of computing. The knowledge of these, and understanding how the components interact together, allow students to design efficient systems that are robust to change and conform to best practice.
Subject details
Learning outcomes
- Apply an information systems framework to determine the type of infrastructure requirements needed for basic data analytic systems.
- Demonstrate the ability to implement basic prototype deployments for big data analytics
- Describe key technical aspects of people, procedures, data, software and hardware as they pertain to data analytic information systems.
- Compare the advantages and disadvantages of basic infrastructure options for data analytic projects.
- Evaluate basic business data infrastructure issues using relevant concepts, models and theories.
- Express business information in a clear, concise writing style tailored to a general audience.
Enrolment requirements
Requisites: |
Nil |
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Assumed knowledge: |
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge. Assumed Prior Learning (or equivalent):Possess demonstrable knowledge in elementary probability theory, statistics, elementary calculus and linear algebra to the level of a unit such as STAT11-112 Quantitative Methods. |
Restrictions: |
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Subject outlines
- January 2025 [Standard - Infrastructure for Data Analytics]
- September 2024 [Standard - Infrastructure for Data Analytics]
- January 2024 [Standard - Infrastructure for Data Analytics]
- September 2023 [Standard - Infrastructure for Data Analytics]
- January 2023 [Standard - Infrastructure for Data Analytics]
- September 2022 [Standard - Infrastructure for Data Analytics]
- January 2022 [Standard - Infrastructure for Data Analytics]
- September 2021 [Standard - Infrastructure for Data Analytics]
- January 2021 [Standard - Big Data Infrastructure]
Subject dates
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January 2024
Standard Offering Enrolment opens: 12/11/2023 Semester start: 15/01/2024 Subject start: 15/01/2024 Cancellation 1: 29/01/2024 Cancellation 2: 05/02/2024 Last enrolment: 28/01/2024 Withdraw - Financial: 10/02/2024 Withdraw - Academic: 02/03/2024 Teaching census: 09/02/2024 -
September 2024
Standard Offering Enrolment opens: 14/07/2024 Semester start: 09/09/2024 Subject start: 09/09/2024 Cancellation 1: 23/09/2024 Cancellation 2: 30/09/2024 Last enrolment: 22/09/2024 Withdraw - Financial: 05/10/2024 Withdraw - Academic: 26/10/2024 Teaching census: 04/10/2024 -
January 2025
Standard Offering Enrolment opens: 10/11/2024 Semester start: 20/01/2025 Subject start: 20/01/2025 Cancellation 1: 03/02/2025 Cancellation 2: 10/02/2025 Last enrolment: 02/02/2025 Withdraw - Financial: 15/02/2025 Withdraw - Academic: 08/03/2025 Teaching census: 14/02/2025
Standard Offering | |
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Enrolment opens: | 12/11/2023 |
Semester start: | 15/01/2024 |
Subject start: | 15/01/2024 |
Cancellation 1: | 29/01/2024 |
Cancellation 2: | 05/02/2024 |
Last enrolment: | 28/01/2024 |
Withdraw - Financial: | 10/02/2024 |
Withdraw - Academic: | 02/03/2024 |
Teaching census: | 09/02/2024 |
Standard Offering | |
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Enrolment opens: | 14/07/2024 |
Semester start: | 09/09/2024 |
Subject start: | 09/09/2024 |
Cancellation 1: | 23/09/2024 |
Cancellation 2: | 30/09/2024 |
Last enrolment: | 22/09/2024 |
Withdraw - Financial: | 05/10/2024 |
Withdraw - Academic: | 26/10/2024 |
Teaching census: | 04/10/2024 |
Standard Offering | |
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Enrolment opens: | 10/11/2024 |
Semester start: | 20/01/2025 |
Subject start: | 20/01/2025 |
Cancellation 1: | 03/02/2025 |
Cancellation 2: | 10/02/2025 |
Last enrolment: | 02/02/2025 |
Withdraw - Financial: | 15/02/2025 |
Withdraw - Academic: | 08/03/2025 |
Teaching census: | 14/02/2025 |