Students

BUSA8031 – Business Analytics Project

2022 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Stefan Trueck
stefan.trueck@mq.edu.au
4 Eastern Road, Room 729
By Appointment
Credit points Credit points
10
Prerequisites Prerequisites
40cp at 8000 level including BUSA8000
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit provides a platform for students to exercise the knowledge and skills that they have gained in previous units in the Master of Business Analytics. The major component of the unit is a project, where students will actively engage with a significant problem or set of problems in the area of analytics. Group work engages students in the challenges of interpersonal communication, task allocation, coordination and control. Students will gain an insight into the analytical problems faced by organisations and be able to contextualise their graduate capabilities into the final business project. The unit will consider key issues, concepts and frameworks of analytics ethics, and social responsibility, and how these can be applied to policy and practice. The class is conducted through lectures, workshops and discussions where students will develop an analytical solution around the client partner's specified information-based problem. Throughout the unit, the emphasis is on the analysis process: identifying information needs, acquiring the necessary information, interpreting it and using it as the basis for strategic recommendations.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Successfully work in teams and reflect on teamwork strategies in achieving group objectives.
  • ULO2: Recognise and apply different perspectives on organisation problems in order to best frame possible solutions.
  • ULO3: Design and conduct an organisational and industry analysis to assess and resolve contextual constraints of a client organisation.
  • ULO4: Deliver an effective and well-justified data analytic solution.
  • ULO5: Examine Business Analytics contribution to individuals, organisations and society and predict the ethical implications relating to the use of data analytics for these stakeholders.

General Assessment Information

Assessment criteria for all assessment tasks will be provided on the unit iLearn site. It is the responsibility of students to view their marks for each within-session-assessment on iLearn within 20 days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment tasks (not including the final exam mark) will not be addressed.

Late submissions of assessments

Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.

No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.

Table 1: Penalty calculation based on submission time

Submission time after the due date (including weekends)

Penalty (% of available assessment task mark)

Example: for a non-timed assessment task marked out of 30

< 24 hours

10%

10% x 30 marks = 3-mark deduction

24-48 hours

20%

20% x 30 marks = 6-mark deduction

48-72 hours

30%

30% x 30 marks = 9-mark deduction

72-96 hours

40%

40% x 30 marks = 12-mark deduction

> 96 hours

100%

Assignment won’t be accepted

Special Consideration

To request an extension on the due date/time for a timed or non-timed assessment task, you must submit a Special Consideration application. An application for Special Consideration does not guarantee approval.

The approved extension date for a student becomes the new due date for that student. The late submission penalties above then apply as of the new due date.

Assessment Tasks

Name Weighting Hurdle Due
Client briefing report 10% No 29/04/22
Participatory Task 10% No weekly throughout the semester
Personal Report 30% No 11/03/22, 01/04/22, 20/05/22
Client Report and Presentation 50% No 02/06/2022

Client briefing report

Assessment Type 1: Professional writing
Indicative Time on Task 2: 10 hours
Due: 29/04/22
Weighting: 10%

 

Students will provide a report on their individual interpretation of the briefing, recognition of potential problems and perspectives on potential solutions, for the client organisation.

 
On successful completion you will be able to:
  • Recognise and apply different perspectives on organisation problems in order to best frame possible solutions.
  • Deliver an effective and well-justified data analytic solution.
  • Examine Business Analytics contribution to individuals, organisations and society and predict the ethical implications relating to the use of data analytics for these stakeholders.

Participatory Task

Assessment Type 1: Participatory task
Indicative Time on Task 2: 10 hours
Due: weekly throughout the semester
Weighting: 10%

 

Students will be required to participate activities in class.

 
On successful completion you will be able to:
  • Recognise and apply different perspectives on organisation problems in order to best frame possible solutions.
  • Deliver an effective and well-justified data analytic solution.
  • Examine Business Analytics contribution to individuals, organisations and society and predict the ethical implications relating to the use of data analytics for these stakeholders.

Personal Report

Assessment Type 1: Report
Indicative Time on Task 2: 25 hours
Due: 11/03/22, 01/04/22, 20/05/22
Weighting: 30%

 

Students will reflect and write three short reports, worth 10% each, regarding the impact the following experiences/topics have had on them: 1) Learning experience across their Master of Business Analytics. 2) Teamwork. 3) Ethics.

 
On successful completion you will be able to:
  • Successfully work in teams and reflect on teamwork strategies in achieving group objectives.
  • Deliver an effective and well-justified data analytic solution.
  • Examine Business Analytics contribution to individuals, organisations and society and predict the ethical implications relating to the use of data analytics for these stakeholders.

Client Report and Presentation

Assessment Type 1: Project
Indicative Time on Task 2: 45 hours
Due: 02/06/2022
Weighting: 50%

 

Students will be required to work in teams on a client organisation issue. Students will be required to: 1) Submit a short group progress report on their progress to date, any issues that have been dealt with and the likely outcomes of their analysis, in the weeks preceding the Client Report and Presentation. 2) Write a professional group report for the client organisation. 3) Deliver a formal presentation to the client organisation. Each student will be individually assessed for their presentation skills (worth 10%).

 
On successful completion you will be able to:
  • Successfully work in teams and reflect on teamwork strategies in achieving group objectives.
  • Recognise and apply different perspectives on organisation problems in order to best frame possible solutions.
  • Design and conduct an organisational and industry analysis to assess and resolve contextual constraints of a client organisation.
  • Deliver an effective and well-justified data analytic solution.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Classes

The unit is comprised of 13 x 3-hour seminars in weeks 1 to 13. Weekly seminars will typically be held in person, but some seminars will also be conducted via Zoom sessions. Seminars may also include recorded content coupled with Zoom Q&A sessions and class activities.

Students are expected to attend the in person scheduled sessions or join the weekly Zoom sessions. The link and passcode for the Zoom sessions will be made available on the iLearn homepage.

Group Work

Group work is an inherent requirement for completing this unit satisfactorily.

Required unit materials and/or recommended readings

Textbook

No formal textbook has been set for this unit. None suits the range of topics introduced here.

Recommended Readings

As a Capstone Unit, we will have some recommended readings included in the iLearn website for this unit so that we can better understand the context in which we are applying our analytical knowledge.

Technology used and required

We will make use of application software tools for predictive and prescriptive analytics as well as data-visualisation software Power BI. An academic license for Power BI is freely available to Macquarie University students in the session.

Unit Web Page

Course material is available on the learning management system (iLearn). The general online website is http://ilearn.mq.edu.au

Unit Schedule

Please refer to iLearn. 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via AskMQ, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2022.04 of the Handbook