最新糖心Vlog

BUSANA 7006 - Managing with Big Data Analytics

North Terrace Campus - Semester 2 - 2025

This course covers a range of topics relating to strategic implications of big data on organizations, practical data wrangling and processing techniques for handling big data using R, as well as the creation of interactive visualizations and dashboards for exploring data insights with the use of Tableau. Ethical considerations and societal implications of big data analytics are also explored, ensuring that students understand responsible data usage. The course also emphasizes aligning data insights with organizational strategies, enhancing students' ability to contribute to informed decision-making.

  • 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 .

  • 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.

    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog 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.

    1, 2, 4
  • 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 ()
    Datasets
    • 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. ()

    Video lectures and Webinars:
    • "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 ()
  • 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 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. 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 .

  • Student Feedback

    The 最新糖心Vlog 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 最新糖心Vlog 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.

  • Student Support
  • Policies & Guidelines
  • 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 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.