The Fundamentals of Analytics module offers a comprehensive introduction to the field of data analytics, examining its foundational principles and its interconnections with machine learning and artificial intelligence. Students will explore various types of data, including structured and unstructured forms, and the associated challenges and opportunities for processing and analysis. The module emphasizes the application of data analytics within different business, organizational, and social contexts, using case studies and literature to illustrate diverse strategies for leveraging data to enhance performance.
The module will cover critical aspects of data analytics including:
- The nature and types of data
- Business, organisational, and social contexts for data analytics
- Legal, ethical, and regulatory considerations
- Data analytics in support of global challenges, such as the Sustainable Development Goals (SDGs)
- Effective communication, group work, and data visualization techniques
Data Overview
- Types and sources of data.
- Data collection methods and challenges.
- The importance of data quality and integrity.
Introduction to Predictive Analytics and Machine Learning
- Basics of predictive modeling and machine learning.
- Supervised vs. unsupervised learning.
- Examples of predictive analytics applications in different fields
- Descriptive analytics and interpretation of historical data to benchmark performance within a business.
- Prescriptive analysis and industry-specific challenges and solutions e.g., supply chain optimisation, financial planning.
Business Context for Data Analytics
- Understanding how data analytics informs and enhances decision-making.
- The significance of analytics in driving strategic business decisions.
- Contextual examples from various industries.
- Cross-disciplinary applications of data analytics.
Ethical Considerations for Data Analytics
- Exploration of ethical issues in data analytics.
- Understanding data privacy laws and regulations.
- Responsible data use and handling ethical dilemmas.
Communication of Data Analytics and Data Visualisation
- Basic types of charts and graphs
- Importance of effective communication in data analytics and design of visualisations.
- Principles of data visualisation and storytelling with data.
- Tools and techniques for creating impactful visualisations.
- Wickham's grammar of graphics
- The role of narrative in idea propagation
- Crafting a compelling story with data
- Structuring your data story
- Visualisation best practices, (accessibility, data-ink ratio)
Global Challenges
- The United Nations' Sustainable Development Goals
- ICT as an enabler for addressing global challenges
- The role of data in progressing the Sustainable Development Goals
The module will be taught with a series of lectures and tutorials. The tutorials will enable students to work together in groups to design the two presentations that they are expected to complete for the module.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |