Learning Outcomes:
After completing this module, students will be able to:
- Audit strategic data ecosystems to determine an organization’s "AI-readiness" and long-term intelligence needs.
- Design secure, scalable frameworks for the collection and governance of high-integrity business data.
- Manipulate complex datasets using AI-enhanced modeling to extract predictive and prescriptive financial insights.
- Command advanced visualization tools to translate raw data into persuasive narratives for executive decision-making.
- Mitigate ethical and security risks, including algorithmic bias and data privacy threats, within automated systems.
Indicative Module Content:
Throughout the module, emphasis is placed on real-world applications, providing a deeper understanding of the intersection between accounting and finance, technology, and data science. Topics covered will include:
1. Strategic Data Landscapes: Appraising organizational data needs and "AI-readiness" to align information strategy with business objectives.
2. Data Governance & Management: Architecting secure frameworks for the collection, cloud storage, and ethical management of high-integrity business data.
3. The Joint Innovation Data Challenge: Engaging with exclusive Central Bank of Ireland and Bank of Italy datasets to solve real-world economic problems.
4. Advanced Analytics & Modeling: Engineering complex datasets using predictive techniques and machine learning to extract actionable financial insights.
5. Visual Storytelling: Commanding visualization tools to translate technical data into persuasive narratives for executive decision-making.
6. Innovation Showcase: Synthesizing findings into a "3-minute thesis" style presentation for an international review panel.
7. Ethics, Privacy & Digital Trust: Addressing the critical challenges of algorithmic transparency, cybersecurity, and data sovereignty in a global regulatory context.