INFS2200: Business Data and AI

2027 unit information

Data is essential to the economy. Data fuels how things work and what you see on your screens. It helps businesses track products, customers, and transactions, and provides them with insights to make better decisions. Data also forms the foundation of AI, since AI is built from data. Becoming knowledgeable about business requires understanding the role of data. In this unit, you'll learn about data as a vital asset, its creation, modelling, structuring, storage in databases, and transfer across systems. You'll explore how to integrate, analyse, and evaluate data to generate actionable insights. Additionally, you'll study how AI models, such as predictive and generative AI, are developed from data. Through practical activities, you'll experiment with AI-supported analysis, assess its strengths and limitations, and design responsible human-AI workflows. Finally, you'll propose AI-driven improvements for business scenarios, considering data, value, risk, and governance. Data and AI are central to modern businesses, enabling organisations to compete by responsibly collecting and using data, deploying AI, and supporting people with technology. By completing this course, you'll gain essential skills for your career as a consultant, business analyst, or entrepreneur.

Unit details and rules

Managing faculty or University school:

Business (Business School)

Details

Study level	Undergraduate
Academic unit	Business Information Systems
Credit points	6

Enrolment rules

Prerequisites: ?	Completion of at least 24 credit points
Corequisites: ?	None
Prohibitions: ?	None
Assumed knowledge: ?	INFS1000 or INFO1000 or INFO1003 or INFO1903

Learning outcomes

At the completion of this unit, you should be able to:

LO1. Critically analyse how various types of business data (structured, semi-structured, and unstructured) influence organisations and evaluate their strategic importance in different environments.
LO2. Integrate and transform diverse data sources to produce meaningful insights.
LO3. Justify the analytical methods used in relation to organisational needs and decision‑making priorities.
LO4. Analyse how modern AI systems interpret, generate, and act on information, and critically evaluate the reliability, risks, and limitations of AI outputs in complex business scenarios.
LO5. Design, refine and critique human‑AI collaboration workflows that enhance organisational problem‑solving, demonstrating responsible oversight, critical judgment, and ethical reasoning.
LO6. Create, present and reflect on a data‑ and AI‑enabled business improvement proposal that synthesises insights, technological capabilities, governance considerations, and ethical implications, providing a well-founded rationale for organisational adoption.

Unit availability

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There are no availabilities for this year.

Session	MoA ?	Location	Outline ?
Semester 1 2027	Normal day	Camperdown/Darlington, Sydney	Outline unavailable
Semester 2 2027	Normal day	Camperdown/Darlington, Sydney	Outline unavailable

There are no availabilities for previous years.

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Modes of attendance (MoA)

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