Module 1: Introduction to Financial Data Analytics

• Overview of financial data sources
• Basics of SQL for data analytics
• Data extraction techniques
• Data cleaning and preprocessing
• Practical session: Importing and cleaning financial data in SQL

Module 2: Exploratory Data Analysis (EDA) in Finance

• Understanding EDA concepts
• Descriptive statistics in financial data
• Identifying patterns and trends
• Anomaly detection in financial data
• Practical session: Conducting EDA on financial datasets in SQL

Module 3: Financial Modeling with Excel

• Introduction to financial modeling
• Building financial statements
• Budgeting and forecasting
• Sensitivity analysis
• Practical session: Creating financial models in Excel

Module 4: Data Visualization with Excel

• Basics of data visualization
• Creating charts and graphs
• Advanced visualization techniques
• Dashboard creation
• Practical session: Visualizing financial data in Excel

Module 5: SQL for Advanced Financial Analysis

• Advanced SQL queries
• Joining and combining data
• Subqueries and common table expressions
• Aggregating financial data
• Practical session: Advanced financial analysis with SQL

Module 6: Time Series Analysis in Finance

• Introduction to time series analysis
• Analyzing stock prices
• Forecasting financial data
• Seasonal decomposition of time series
• Practical session: Time series analysis using SQL and Excel

Module 7: Risk Analysis and Management

• Basics of risk analysis
• Value at Risk (VaR) calculation
• Stress testing
• Scenario analysis
• Practical session: Risk analysis in Excel

Module 8: Financial Performance Analysis

• Key performance indicators (KPIs)
• Ratio analysis
• Benchmarking
• Trend analysis
• Practical session: Analyzing financial performance in Excel

Module 9: Portfolio Management and Optimization

• Basics of portfolio management
• Diversification and asset allocation
• Portfolio optimization techniques
• Performance evaluation
• Practical session: Portfolio optimization using Excel

Module 10: Data Integration and Reporting

• Combining multiple data sources
• Data integration techniques
• Creating interactive reports in Excel
• Reporting and presentation skills
• Practical session: Integrating and reporting financial data

Module 11: Advanced Financial Modeling

• Introduction to advanced modeling techniques
• Scenario analysis in financial models
• Monte Carlo simulation
• Optimization in financial modeling
• Practical session: Advanced financial modeling in Excel

Module 12: Machine Learning Applications in Finance

• Basics of machine learning
• Supervised learning techniques
• Unsupervised learning techniques
• Real-world applications in finance
• Practical session: Building machine learning models in Excel

Module 13: Financial Data Governance and Compliance

• Understanding data governance
• Regulatory requirements
• Data quality management
• Implementing compliance measures
• Practical session: Addressing governance and compliance issues

Module 14: Case Studies in Financial Data Analytics

• Review of successful case studies
• Lessons learned from real-world projects
• Best practices in financial data analytics
• Developing a project plan
• Practical session: Analyzing case studies and project planning

Module 15: Scenario Analysis and Decision Support

• Introduction to scenario analysis
• Developing financial scenarios
• Decision support systems
• Implementing scenario analysis in SQL and Excel
• Practical session: Conducting scenario analysis

Module 16: Data Ethics and Privacy in Finance

• Understanding data ethics
• Data privacy regulations
• Ethical considerations in data analysis
• Implementing data privacy measures
• Practical session: Addressing ethical issues in financial data

Module 17: Advanced Excel Techniques

• Advanced features in Excel
• Custom calculations and parameters
• Advanced chart types
• Dashboard interactivity and design
• Practical session: Creating advanced visualizations in Excel

Module 18: Capstone Project

• Integrating all learned concepts
• Designing a comprehensive project
• Data analysis and visualization
• Presentation of project findings
• Practical session: Capstone project execution and presentation

Trainer Experience

Our trainers are industry experts with extensive experience in financial data analytics, SQL programming, and Excel. They have successfully led numerous projects and have a deep understanding of the challenges and opportunities in the field.

Quality statement

We are committed to providing high-quality training that meets the needs of our participants. Our courses are designed to be practical, interactive, and relevant to current industry trends.

Tailor-made courses

We offer tailor-made courses to suit the specific needs of organizations. Contact us to discuss your requirements and how we can customize the training for your team.

Payment

A week before the training starts.

Accommodation and airport pick-up

We provide assistance with accommodation and airport pick-up for participants traveling from outside Nairobi. Please contact us for more information.