Data Analysis with Databricks for Finance Training Course

Introduction to Databricks and Financial Applications

• Exploring the Databricks ecosystem.
• An overview of financial data analysis workflows.
• Case studies: risk modeling, financial reporting, and audit logs.

Getting Started with Databricks Notebooks

• Creating and navigating through notebooks.
• Utilizing Python and SQL within Databricks.
• Collaborating through comments and version history tracking.

Data Ingestion and Cleaning

• Importing financial data from CSVs, databases, and APIs.
• Employing Spark DataFrames for data cleaning and preparation.
• Addressing missing values and identifying outliers.

Transforming and Aggregating Financial Data

• Calculating key performance indicators (KPIs) and financial ratios.
• Filtering, grouping, and pivoting datasets for deeper analysis.
• Manipulating and resampling time series data.

Visualizing Financial Insights

• Building dashboards using Databricks visual tools.
• Customizing charts to meet finance reporting requirements.
• Exporting visuals for presentations or regulatory compliance reviews.

Optimizing Queries and Utilizing Delta Lake

• An introduction to Delta Lake architecture.
• Understanding ACID transactions and ensuring data reliability.
• Enhancing performance through data partitioning strategies.

Collaboration, Scheduling, and Sharing

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

Summary and Next Steps