Undergraduate SWI-INF30030-2022

Business Analytics

Forecast 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.

Duration

13 weeks

Study method

100% Online

Available loans

HECS-HELP
FEE-HELP

Assessments

100% online

Prior study

Required

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2022

Subject details

What you'll learn

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.

Topics covered

- 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

Entry requirements

You must have successfully completed the following subject(s) before starting this subject:

SWI-INF10003-Introduction to Business Information Systems (No longer available)

Others

200 credit points Assumed Knowledge - Basic understanding of computer programming

Additional requirements

No additional requirements

Description

Students will develop and enhance their conceptual and practical understanding in data analytics in a business context. Students will have an opportunity to immerse themselves in problem-solving activities requiring lateral and critical thinking by exploring structured and unstructured data, considering and applying the appropriate analytic techniques using a software programming environment for statistical computing (such as R) and visualisation tools and approaching organisational problems through data-driven decision-making processes.

Assessments

Presentation, reports and journals Initial Project Plan Project Management Presentations Final report and Solution(s)

Individual/Group (100%)

Textbooks

Current study term: 28 Aug 22 to 27 Nov 22

Check the learning management system (LMS) of your university for textbook details.