The unit is concentrated on big data oriented learning and practices. In order for organisations to gain a competitive advantage, industry practitioners are required to be able to predict anomalies, disorders or indicators from their business categorical and numerical data that could lead to capture appropriate insights for their effective decision making.
Emerging technologies to various successful analytics systems implementation are continuously evolving to make effective predictions for quick decision support. This unit provides students with the knowledge and skills to utilise predictive analytics and data mining processes and technologies to gain greater insights into various business scenarios. Students will gain an overview of foundational knowledge on various applications of predictive analytics tools and techniques for enabling action-able decision solutions supported by industry case studies and hands-on exercises. Students will learn how data mining and predictive analytics can facilitate business intelligence and build analytical capabilities in organisations in the 21st century.
Emerging technologies to various successful analytics systems implementation are continuously evolving to make effective predictions for quick decision support. This unit provides students with the knowledge and skills to utilise predictive analytics and data mining processes and technologies to gain greater insights into various business scenarios. Students will gain an overview of foundational knowledge on various applications of predictive analytics tools and techniques for enabling action-able decision solutions supported by industry case studies and hands-on exercises. Students will learn how data mining and predictive analytics can facilitate business intelligence and build analytical capabilities in organisations in the 21st century.
Unit details
Location:
Study level:
Postgraduate
Credit points:
12
Unit code:
BCO6008
Prerequisites
BCO7000 - Business Analytics and Visualisation
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Learning Outcomes
| 1. | Contextualise the art and science of predictive analytics to define clear actions that result in improved decisions and business results for contemporary organisations and dynamic communities locally and globally; | ||
| 2. | Validate the selection, preparation, construction, integration, structure, and formatting of data as effective to ensure predictive models meet the business goals; | ||
| 3. | Appraise appropriate goals for a predictive analytics implementation in organisations and authenticate recommendations with reference to a specified organisation's strategic priorities and mission and values statements and anticipated changing environment; | ||
| 4. | Critically review the use and assist in the selection of industry standard analytics tools and investigate the application of sources of information including social media data, unstructured text and/or big data sets to provide greater insight to business; and; | ||
| 5. | Interpret conclusions to inter-disciplinary audiences demonstrating a high level of personal autonomy and accountability in achieving group outcomes. |
Assessment
| Assessment type | Description | Grade |
|---|---|---|
| Test | In-class test - Problem solving and short answers | 25% |
| Assignment | Case studies and predictive modelling | 35% |
| Report | Research Report (Group) | 40% |
Where to next?
As part of a course
This unit is studied as part of the following courses. Refer to the course page for information on how to apply for the course.
You can choose to study this unit as part of the following courses. Refer to the course page for information on how to structure your course to include this unit.
| Course | Study as part of |
|---|---|
| Graduate Diploma in Business | Business Analytics and Visualisation - Specialisation |
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