Business Analytics

Subject BUSA90493 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

April, Parkville - Taught on campus.
Pre-teaching Period Start 04-Apr-2016
Teaching Period 11-Apr-2016 to 19-Jun-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 05-Apr-2016
Census Date 22-Apr-2016
Last date to Withdraw without fail 27-May-2016

August, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 25-Aug-2016 to 11-Nov-2016
Assessment Period End 18-Nov-2016
Last date to Self-Enrol 09-Sep-2016
Census Date 16-Sep-2016
Last date to Withdraw without fail 21-Oct-2016

This subject is only available to students admitted to MC-BA, MC-BAPT, or students with permission of the MBA course coordinator

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 30 hours
Total Time Commitment: Not available
Prerequisites: None
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:


Melbourne Business School

Degree Program Services


Subject Overview:

The aim of Business Analytics is to teach students how to extract relevant information from data to make improved business decisions.

Big data is big business, but there are not enough managers who can ask the right questions and interpret the results of analysis effectively. The McKinsey report predicts a need for an additional 1.5 million adequately trained managers in the US alone. Business Analytics is the science of extracting useful information from datasets, large and small. It is also about knowing which type of data to use for solving a business problem, and how to influnece the organisation to move from a 'decision-based evidence making' mode to an 'evidence-based decision-making' mode.

Learning Outcomes:

On completion of this subject the student should be able to:

  • Convert raw data into relevant information for management decisions
  • Describe and visualise their data
  • Provide a diagnosis of the data generation process
  • Predict future outomes, and prescribe appropriate management action based on those predictions
  • Develop presentation skills to convey this information to non-technical audiences
  • Contribution to class learning, throughout the term (10%)
  • Syndicate assignment, equivalent to 500 words individually, due Weeks 5-6 (30%)
  • 5 Quizzes, collectively equivalent to 1500 words, held biweekly from Week 2 (20%)
  • Final exam, equivalent to 2500 words, held end of term (40%)
Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date

This subject is only available to students admitted to MC-BA, MC-BAPT, or students with permission of the MBA course coordinator

Related Course(s): Master of Business Administration
Master of Business Administration
Master of Business Administration/Master of Marketing

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