Enrolments for 2018 have closed.
Business Analytics
Undergraduate | SWI-INF30030 | 2018
Course information for 2018 intake
View information for 2019 course intakeForecast business scenarios and plan solutions that can be applied in a real-life setting. Get hands-on with cloud, mobile and enterprise resource planning software. See where the analyst fits into different business divisions and management levels.
- Study method
- 100% online
- Assessments
- 100% online
- Entry requirements
- Prior study needed
- Duration
- 13 weeks
HECS-HELP and FEE-HELP available
Business Analytics
About this subject
Students who successfully complete this subject will be able to:
- Demonstrate an understanding of the critical roles of business analytics in various organisational contexts
- Synthesise and develop appropriate business solution scenarios using appropriate analytics and visualisation techniques
- Analyse business problems and define the data requirements and business rules associated with the data-driven problem-solving approaches
- Demonstrate critical thinking and problem solving
- Communicate effectively as a professional and function as an effective leader or member of a diverse team.
- Use of and value of analytics in Business divisions, management functions, different management levels, performance management
- Business rules vs business data requirements
- Marketing analytics, financial analytics, sports analytics, geospatial analytics, security analytics, health analytics, SNA, etc.
- Multi-platform analytics (mobile, cloud, ERP)
- Data visualisation, dashboard design, storyboarding with analytics
- Data-driven decision making vs Intuitive decision making
- Introduction to advance analytics: Predictive, Prescriptive, CI, sentiment analytics, geospatial analytic
- Forecasting and predictive analytics, scenario planning
- Fast data, data lake, social media data, open data
This subject aims to develop and enhance students’ conceptual and practical understanding in Business Analytics in a business context. Students will have an opportunity to immerse themselves in a problem-solving activities requiring lateral and critical thinking by exploring Big Data, considering and applying the appropriate analytic techniques and/or tools, and approach an organisational problem through data-driven decision making process.
- Individual/Group (100%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
Prior study
You must have successfully completed the following subject(s) before starting this subject:
one of
- SWI-INF10002-Database Analysis and Design
SWI-INF20004 (Not currently available)
Others
You must also complete 87.5 credit points (7 OUA subjects) before undertaking this subject.
Additional requirements
No additional requirements
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
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