LEO5302 · Data and analytics in organisations and society

Overview

Around the globe and spanning sectors, data and data analytics permeate all aspects of organisational operations – data has become ubiquitous to organisational domains. The widespread use of data and analytics pose unique challenges that managers must consider when making decisions and enacting change. This unit will provide an overview of contemporary issues surrounding the utility of data and analytics. This unit advances understanding of the commercial, economic, social, legal, and ethical considerations for the use of data and analytics. Frameworks and models on data governance are introduced for building accountability to maximise proper usage of analytics tools, including generative AI. Real-world case studies illustrate effective use of analytics and data-driven intelligence generation along with potential undesirable and unintended consequences. With specific attention on cases that have made many wary of the role of data in society (e.g., Google’s continuous data harvesting), the unit also explores the “dark side” of data analytics and artificial intelligence. As such, the unit prepares managers to make informed and discerning judgments about the consequences of using data and data-driven intelligence tools for specific goals within organisations and society.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. deliberate issues related to data analytics through real world case studies and its impact on organisations and society
2. assess issues regarding the use of data and the need for data governance frameworks and standards in organisations to enhance data protection
3. review the risks and benefits associated with the utilisation of data and its derived products, taking into account crucial economic, legal, and ethical considerations.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.