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This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.
Big Data and associated data analytics are emerging as important technology resources that management and executives are attempting to utilise to facilitate their decision-making, especially when identifying trends or patterns in large amounts of data is required to resolve strategic or operational directions. Nevertheless, surveys by industry researchers report that, while enterprises and SMEs are eager to use these resources, they struggle to understand what tangible benefits they might bring for their specific business and how to implement them to deliver those benefits. This unit aims to develop and enhance students’ conceptual and practical understanding of Big Data and Data Analytics in a business context, and tackle the many issues that are associated with deploying these resources such as information governance, privacy, security, ethical considerations, understanding the value of a company’s data and developing a business case to implement these resources.
The unit shall be offered in the following modes/locations External (online). Delivery of the unit through an external delivery pattern will occur across traditional semesters. Block (weekend) – Block delivery involves online delivery of material (TEL), coupled with two complete weekends that are separated by a number of weeks. The material delivered via TEL will occur prior to the first block weekend and between the two weekend blocks of face to face teaching. Intensive (week long day classes) – Intensive delivery of material will occur over a number of consecutive days (normally five or six) of teaching. The student will be supported through appropriate TEL.
Equivalent to MBA6045
On completion of this unit students should be able to:
Students will attend on campus classes as well as engage in learning activities through ECU's LMS
| Joondalup | Mount Lawley | South West (Bunbury) | |
|---|---|---|---|
| Semester 2 | 13 x 3 hour seminar | Not Offered | Not Offered |
For more information see the Semester Timetable
Students will engage in learning experiences via ECU’s LMS as well as additional ECU learning technologies
GS1 GRADING SCHEMA 1 Used for standard coursework units
Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.
| Type | Description | Value |
|---|---|---|
| Case Study | Review of a Case Study | 20% |
| Presentation | Data analytics business use case presentation | 30% |
| Report | Develop a business case for data analytics | 50% |
| Type | Description | Value |
|---|---|---|
| Case Study | Review of a Case Study | 20% |
| Presentation | Data analytics business use case presentation | 30% |
| Report | Develop a business case for data analytics | 50% |
For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.
Students please note: The marks and grades received by students on assessments may be subject to further moderation. Informal vivas may be conducted as part of an assessment task, where staff require further information to confirm the learning outcomes have been met. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.
Integrity is a core value at Edith Cowan University, and it is expected that ECU students complete their assessment tasks honestly and with acknowledgement of other people's work as well as any generative artificial intelligence tools that may have been used. This means that assessment tasks must be completed individually (unless it is an authorised group assessment task) and any sources used must be referenced.
Breaches of academic integrity can include:
Copying the words, ideas or creative works of other people or generative artificial intelligence tools, without referencing in accordance with stated University requirements. Students need to seek approval from the Unit Coordinator within the first week of study if they intend to use some of their previous work in an assessment task (self-plagiarism).
Working with other students and submitting the same or substantially similar work or portions of work when an individual submission was required. This includes students knowingly providing others with copies of their own work to use in the same or similar assessment task(s).
Organising a friend, a family member, another student or an external person or organisation (e.g. through an online website) to complete or substantially edit or refine part or all of an assessment task(s) on their behalf.
Using or having access to unauthorised materials in an exam or test.
Serious outcomes may be imposed if a student is found to have committed one of these breaches, up to and including expulsion from the University for repeated or serious acts.
ECU's policies and more information about academic integrity can be found on the student academic integrity website.
All commencing ECU students are required to complete the Academic Integrity Module.
In some circumstances, Students may apply to their Unit Coordinator to extend the due date of their Assessment Task(s) in accordance with ECU's Assessment, Examination and Moderation Procedures - for more information visit https://askus2.ecu.edu.au/s/article/000001386.
Students may apply for Special Consideration in respect of a final unit grade, where their achievement was affected by Exceptional Circumstances as set out in the Assessment, Examination and Moderation Procedures - for more information visit https://askus2.ecu.edu.au/s/article/000003318.
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