• Types of data analytics and their applications in finance
• Understanding data sources and the importance of data accuracy and control
• Understanding big data: value, technology, skills, strategy, and its role in finance
• Introduction to data mining and the CRISP-DM framework

• Understanding core concepts and methodologies of data science, including ethics and the impact of data in finance and accounting.
• Managing data
• Understanding algorithms and big data processing
• Tools for data preparation

• Understanding different data types and analytical approaches
• Exploring descriptive, predictive, and prescriptive analytics
• An introduction to regression analysis 
• Avoiding common mistakes in data analysis

• Overview of key techniques
• Cluster analysis
• Time series analysis
• Applying analytics in finance and accounting
• Monte Carlo Simulation

• Foundations of data visualisation
• Essential tools for data analysis and visualisation
• Core concepts and techniques in data visualisation
• The value of data visualisation for finance professionals

6. Ensuring meaningful visualisation

• Planning and creating effective data presentations and reports
• Reporting performance with measures, indicators, and charts
• Using run charts, control charts, and pareto charts for clear data interpretation
• Tailoring reports for specific audiences

• Introduction to Business Intelligence (BI) tools
• Developing essential professional skills
• Integrating BI with financial strategy
• Data-Driven Decision Making
• Performance metrics and KPIs 

• Understanding data governance frameworks
• Regulatory compliance
• Data privacy and security measures
• Implementing data management frameworks