BUSANA 7006 - Managing with Big Data Analytics
North Terrace Campus - Semester 2 - 2025
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General Course Information
Course Details
Course Code BUSANA 7006 Course Managing with Big Data Analytics Coordinating Unit Adelaide Business School Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Available for Study Abroad and Exchange Y Course Staff
No information currently available.
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
At the completion of this course students are expected to be able to:
CLO1: Analyse large datasets using advanced data processing techniques to achieve accurate and reliable insights.
CLO2: Construct interactive visualizations to communicate complex data insights effectively to diverse stakeholders to facilitate informed decision-making and strategic planning.
CLO3: Identify and address ethical dilemmas, ensuring responsible and transparent use of data within organizational contexts.
CLO4: Leverage AI algorithms and models to enhance data processing and predictive modelling accuracy, in alignment with organisational objectives and industry best practices.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1, 2, 4 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
1, 2 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
4 Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
3 Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
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Learning Resources
Recommended Resources
Case studies:- MIT Sloan Management Review ()
- Harvard Business Review ()
- Gartner Business Quarterly () It provides business executives with insights from best practices research and the real-world experience of practitioners.
- General Data Protection Regulation (GDPR) of the EU ()
- Microsoft’s Data Governance: ()
- Facebook and Cambridge Analytica Scandal ()
- Google’s Project Nightingale ()
- Enriching KYB and KYC with multi-source data ()
- Telstra workforce culling ()
- Optus Data Breach ()
- Kaggle () - A platform for data science competitions and datasets, where students can practice their data analysis skills on real-world problems.
- Data.gov () - A repository of government datasets that can be used for practicing data wrangling, analysis, and visualization.
Online Learning
Online Textbooks-
"R for Data Science" by Hadley Wickham and Garrett Grolemund. ()
- "Introduction to R for Data Science" by David Langer - A series of video lectures introducing R programming for data analysis. ()
- "Tableau Training" by Tableau – Free subscription and online tutorials for students ()
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Learning & Teaching Activities
Learning & Teaching Modes
No information currently available.
Workload
No information currently available.
Learning Activities Summary
No information currently available.
Specific Course Requirements
Although no prior knowledge or experience is required, students are expected to type and run R code on R Studio. Therefore, they need to bring a laptop with an internet connection and a charger to the classroom. There is no requirement to subscribe to any of the paid versions of the online platforms or tools (e.g., Tableau) outlined above.It is advisable to invest in a good set of headphones (with an integrated microphone), as there are likely times when you will need to engage in online collaboration with others. -
Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
This course contains three types of assessments:
Assessment Task Assessment Type Due Date CLOs being assessed Assessment Weighting Take-home Quizzes Formative and Summative Throughout the teaching period with deadlines set for each piece of work a day before the following teaching session. 2, 3, 4 20% Group Assignment Summative Refer to the announcement about assignment schedule 1, 2, 3, 4 30% Final Exam Summative Refer to the announcement about assignment schedule 1, 2, 3, 4 50% Assessment Detail
No information currently available.
Submission
No information currently available.
Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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Fraud Awareness
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.
The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
