Data Analysis with Databricks for Finance Training Course

Foundations of Databricks and Financial Applications

• Exploring the Databricks ecosystem
• Reviewing workflows for financial data analysis
• Case studies: risk modeling, financial reporting, and audit logs

Initiating Work with Databricks Notebooks

• Creating and managing notebooks
• Utilizing Python and SQL within Databricks
• Collaborating via comments and tracking version history

Data Ingestion and Preprocessing

• Importing financial data from CSV files, databases, and APIs
• Employing Spark DataFrames for data cleaning and preparation
• Addressing missing values and outliers

Processing and Summarizing Financial Data

• Deriving KPIs and financial ratios
• Filtering, grouping, and pivoting datasets
• Manipulating and resampling time series data

Visualizing Financial Insights

• Developing dashboards using Databricks visualization tools
• Customizing charts for financial reporting
• Exporting visualizations for presentations or regulatory compliance

Query Optimization and Delta Lake Integration

• Overview of Delta Lake architecture
• ACID transactions and ensuring data integrity
• Enhancing performance through data partitioning

Team Collaboration, Scheduling, and Distribution

• Managing access controls and permissions for finance teams
• Setting up scheduled jobs for automated reporting
• Securely exporting data and outcomes

Conclusion and Future Directions