Data Analysis with Databricks for Finance Training Course

Foundations of Databricks and Financial Applications

• Navigating the Databricks ecosystem
• Understanding workflows in financial data analysis
• Case studies: risk modelling, financial reporting, and audit trail management

Commencing with Databricks Notebooks

• Creating and managing notebooks
• Implementing Python and SQL within Databricks
• Enhancing collaboration through comments and version control

Data Ingestion and Data Cleaning

• Importing financial data from CSV files, databases, and APIs
• Utilising Spark DataFrames for data cleansing and preparation
• Managing missing values and outliers effectively

Transformation and Aggregation of Financial Data

• Computing Key Performance Indicators (KPIs) and financial ratios
• Applying filters, grouping, and pivoting to datasets
• Manipulating and resampling time series data

Visualising Financial Insights

• Building dashboards using Databricks' visualisation tools
• Customising charts for financial reporting standards
• Exporting visuals for presentations or regulatory compliance reviews

Query Optimisation and Delta Lake Implementation

• Understanding Delta Lake architecture
• Ensuring data reliability through ACID transactions
• Enhancing performance via data partitioning strategies

Collaboration, Automation, and Distribution

• Administering access controls and permissions for finance teams
• Scheduling automated jobs for regular reporting
• Securely exporting data and analytical results

Recap and Future Directions