Students

BUSA3020 – Advanced Analytics Techniques

2023 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Elias Maroun
elias.maroun@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
(STAT270 or STAT2170) and (MGMT220 or BUSA2020)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This is an advanced applied-skills unit which extends concepts and analytical techniques from earlier units. Students will use data to create graphical representations of data for analysis. Students will clean data in commonly-used spreadsheet formats and make extensive use of proprietary software from big-data orientated companies. Students will develop skills in data visualisation that can be applied to competitive behaviour, target customer analysis, criminology and security intelligence problems.

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: Develop sound solutions to a range of business problems using an analytical approach.
  • ULO2: Demonstrate competence in applying basic forecasting techniques to a range of business issues.
  • ULO3: Apply critical thinking to strategy in analysing firm behaviour.
  • ULO4: Analyse contemporary challenges commonly facing business organisations and how to respond to them.

General Assessment Information

“Late Assessment Submission Penalty (written assessments) 

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern.  

For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.”

Assessment Tasks

Name Weighting Hurdle Due
Clustering & Segmentation 20% No Week 11
Predictive Analytics 20% No Week 7
Group Project 40% No Week 13
Cleaning and dealing with messy data 20% No Week 4

Clustering & Segmentation

Assessment Type 1: Practice-based task
Indicative Time on Task 2: 15 hours
Due: Week 11
Weighting: 20%

 

Applying appropriate clustering techinques to find meaningful groups and make business recommendations based on the found relationship.

 
On successful completion you will be able to:
  • Demonstrate competence in applying basic forecasting techniques to a range of business issues.
  • Apply critical thinking to strategy in analysing firm behaviour.
  • Analyse contemporary challenges commonly facing business organisations and how to respond to them.

Predictive Analytics

Assessment Type 1: Practice-based task
Indicative Time on Task 2: 20 hours
Due: Week 7
Weighting: 20%

 

Implementing multiple predictive models to forecast a target variable. Comparing and contrasting forecasting performances.

 
On successful completion you will be able to:
  • Apply critical thinking to strategy in analysing firm behaviour.
  • Analyse contemporary challenges commonly facing business organisations and how to respond to them.

Group Project

Assessment Type 1: Report
Indicative Time on Task 2: 35 hours
Due: Week 13
Weighting: 40%

 

Data wrangling and Predictive analysis: Group will work together on an allocated project/case and submit python code, recorded video explanations of their solutions and a written group report.

 
On successful completion you will be able to:
  • Develop sound solutions to a range of business problems using an analytical approach.
  • Apply critical thinking to strategy in analysing firm behaviour.
  • Analyse contemporary challenges commonly facing business organisations and how to respond to them.

Cleaning and dealing with messy data

Assessment Type 1: Practice-based task
Indicative Time on Task 2: 15 hours
Due: Week 4
Weighting: 20%

 

Data cleaning, encoding ordinal and nominal variable, and dealing with missing values. Making forecasts based on messy datasets.

 
On successful completion you will be able to:
  • Develop sound solutions to a range of business problems using an analytical approach.
  • Demonstrate competence in applying basic forecasting techniques to a range of business issues.

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

  • Number and length of classes: 3 hours face-to-face teaching per week, consisting of 1 x 2 hour lecture and 1 x 1 hour tutorial.
  • The timetable for classes can be found on the University web site at: http://www.timetables.mq.edu.au/

Recommended Textbook

  • Python Machine Learning (Third Edition) by Raschka and Mirjalili
  • Business Analytics A Management Approach, 2019, Vidgen, Kirshner & Tan, Macmillan International Paperback - 9781352007251

Technology Used and Required

  • You will need a decent quality laptop (a tablet will not be enough)
  • Students will mainly use Python and Jupyter Lab
  • Other technologies that may be used include Data Mining/Analytics packages

 

Unit Schedule

Available on 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 2023.04 of the Handbook