Data Analytics for Business
The Data Analytics for Business specialisation enables students to master the tools of quantitative analysis and apply them in a business setting. This involves building models of business problems and analysing business data.
In today’s business environment where “the world’s most valuable resource is no longer oil but data”, businesses need more and more people with skills to extract insight from data and turn it into profit potential.
Students will be able to utilise techniques from optimisation, statistics and artificial intelligence, together with business knowledge, to assist in business decision making.
This specialisation provides opportunities to apply responsibly sophisticated analytical approaches to many different functional areas, such as accounting, marketing, finance and operations.
Requirements for a Data Analytics for Business specialisation
To achieve a specialisation in Data Analytics for Business within the Master of Commerce and Master of Commerce (Extension), students must complete 30 credit points in units of study comprising:
- 6 credit points in Table A - Foundational units of study; and
- 6 credit points of Table A – Business Analytics for Business core units of study; and
- 18 credit points of Table A- Business Analytics for Business selective units of study.
Students completing this specialisation to meet the requirements for the Master of Commerce or as their compulsory specialisation for the Master of Commerce (Extension) would complete a 6 credit point capstone unit from Table A – Capstone units of study for their degree in the same subject area as their specialisation.
Students completing this specialisation as their optional second specialisation for the Master of Commerce (Extension) are not required to complete a capstone unit of study.
Sample pathways
(i) Master of Commerce
A sample pathway for the Data Analytics for Business specialisation spread over the three semesters of the Master of Commerce degree (Full-time study) is listed below.
| Session |
Units of study | ||
|---|---|---|---|
| 1st Semester |
Foundational: QBUS5001 Foundation in Data Analytics for Business | Specislisation selective | |
| 2nd Semester |
Specialisation core: BUSS6002 Data Science in Business |
Specailisation selective | |
| 3rd Semester |
Specialisation selective | ||
(ii) Master of Commerce (Extension)
A sample pathway for the Data Analytics for Business specialisation spread over 2 years of the Master of Commerce (Extension) degree (Full-time study) is listed below.
| Session |
Units of study | |
|---|---|---|
| 1st Semester |
Foundational: QBUS5001 Foundation in Data Analytics for Business | |
| 2nd Semester |
Specialisation core: BUSS6002 Data Science in Business | |
| 3rd Semester |
Specialisation selective | Specialisation selective |
| 4th Semester |
Specialisation selective | |
Please Note. This sample progression is meant as an example only. Depending on unit prerequisites, students may be able to complete these units in a different sequence to that displayed in the table above.
For details of the units of study required for the specialisation please refer to the Table A- Data Analytics for Business section under Commerce Subject Areas in this handbook.
Learning Outcomes
| Mid-Level Learning Outcomes - Data Analytics for Business specialisation | |
|---|---|
| 1 | Appraise a range of advanced data analytic theories and concepts to apply correct approach to investigating a business problem. |
| 2 | Create analytic models and algorithms using contemporary software and by applying appropriate business analytics knowledge and techniques. |
| 3 | Critically evaluate information, data and research from a range of academic sources and media, to identify bias in decision making. |
| 4 | Communicate the results of advanced technical analysis effectively to any audience via appropriate oral, visual or written formats. |
| 5 | Synthesise advanced data analytic knowledge with wider business theories to generate creative solutions to complex business problems. |
| 6 | Integrate different perspectives from diverse teams to generate new insights and lead positive change in decision making. |
| 7 | Develop ethical and sustainable solutions to ambiguous and uncertain business problems using advanced analytic theories and concepts. |
Further information
For further information regarding study in data analytics in business in the Commerce coursework programs, please contact the Discipline of Business Analytics.