Business Analytics

Bachelor of CommerceMajorYear: 2025

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Overview

The of use of increasingly diverse forms and large amounts of data in business intelligence and decision making has been increasingly integral to achieving and sustaining competitive advantage.

Decision makers in business organisations, public sector organisations and policy makers are reliant on business analyst professionals who can identify useful data for generating new insights, structuring and interpreting the data, and communicating their analysis to nontechnical users and decision makers.

Graduates with a major in Business Analytics have varied employment opportunities in both the public and private sector in a rapidly expanding set of professional applications. Data analytics working across different industry and organisational settings combine knowledge and skills from core business and economics disciplines, such as accounting, actuarial studies, economics, finance, human resource management, operations and supply chain management, and marketing, with techniques that rely on computational science, including algorithms, natural language programming, artificial intelligence, and quantum computing.

Competing the major in Business Analytics, students will learn about core techniques deployed to identify, evaluation and resolution of complex business and economics problems.  This major offers a strong complement to other existing majors within the Bachelor of Commerce, which provide the theories, models and techniques relevant to particular professional fields. 

Intended learning outcomes

On completion of this major, students should be able to:

  • Identify diverse data sources and types and explain their value for generating new insight and informing decisionmaking and solving business and public policy problems;
  • Critically assess the potential misuse and abuse of data analytics, the limitations, and ethical, professional, and legal obligations;
  • Integrate context, frameworks, and datasets to conceptualise the application of data and artificial intelligence for business and policy decision-making;
  • Acquire and manage data to undertake diverse analytics and computational procedures that enable problem identification, description, analysis, and decision-making;
  • Apply simulation techniques to critically evaluate potential solutions to business and public policy problems and optimise decision-making;
  • Identify the most appropriate frameworks, methods and project design for addressing computational challenges. establishing causality, making predictions, and applying those methods to inform decision-making across various business functions and public policy problems; and
  • Summarise, visualise, and interpret data to inform actionable outcomes that can be communicated to non-experts and deployed in business and public policy contexts.

Last updated: 27 February 2025

Structure

75 credit points

To obtain a major in Business Analytics students need to complete:

  • 37.5 credit points of foundation subjects
  • Between 12.5 and 25 credit points of Level 3 core subjects
  • A maximum of 12.5 credit points of Elective subjects
  • 12.5 credit points of capstone subjects

Subject lists

Foundation subjects

Code Name Study period Credit Points
CMCE10002 Foundations of Business Analytics
Semester 2 (On Campus - Parkville)
 12.5
BUSA20001 Visualisation and Data Wrangling
Semester 2 (On Campus - Parkville)
 12.5
MAST20034 Critical Thinking with Data
Semester 2 (On Campus - Parkville)
 12.5

Level 3 core subjects

Code Name Study period Credit Points
CMCE30002 Business Data Governance and Ethics Not available in 2025 12.5
CMCE30004 Unstructured Data Analytics for Business Not available in 2025 12.5
CMCE30003 Machine Learning & AI for Business Not available in 2025 12.5

Level 3 elective subjects

Code Name Study period Credit Points
ACCT30001 Analysis of Firms & Financial Statements
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
ACCT30002 Enterprise Performance Management
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
ACTL30008 Actuarial Analytics and Data I
Semester 1 (On Campus - Parkville)
 12.5
ECOM30001 Basic Econometrics
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
ECOM30002 Econometrics 2
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
ECOM30003 Applied Microeconometric Modelling
Semester 2 (On Campus - Parkville)
 12.5
ECOM30004 Time Series Analysis and Forecasting
Semester 2 (On Campus - Parkville)
 12.5
ECON30025 Computational Economics and Business
Semester 1 (On Campus - Parkville)
 12.5
FNCE30010 Algorithmic Trading
Semester 2 (On Campus - Parkville)
 12.5
MKTG30014 Data Driven Marketing Not available in 2025 12.5
MGMT30020 Analytics for Supply Chain & Operations Not available in 2025 12.5
MGMT30021 Human Resource Analytics Not available in 2025 12.5
FNCE30014 Machine Learning in Finance
Semester 2 (On Campus - Parkville)
 12.5

Capstone subject

Code Name Study period Credit Points
CMCE30005 Business Analytics Challenge Not available in 2025 12.5

Last updated: 27 February 2025