A comprehensive personal finance management system that combines a powerful Google Sheets dashboard with Python-based data analysis capabilities. This project showcases my expertise in financial data processing, API integration, and modern data analysis techniques.
- Interactive Budgeting Dashboard: A feature-rich Google Sheets template for tracking, categorizing, and visualizing personal finances
- Automated Data Pipeline: Python-based ETL (Extract, Transform, Load) system that integrates with Google Sheets API
- Advanced Financial Analysis: Custom analytics module for deriving actionable insights from financial data
- Automated Data Import: Secure OAuth2 authentication with the Google Sheets API to fetch and update financial data
- Robust Data Processing: Comprehensive data cleaning and transformation pipeline using pandas
- Financial Analysis Tools: Custom functions for expense categorization, trend analysis, and financial ratio calculations
- Error Handling & Logging: Production-grade error handling with detailed logging for troubleshooting
- Type Safety: Static type checking with Python type hints for increased code reliability
- Google Sheets Mastery: Advanced formulas, conditional formatting, and custom dashboard design
- API Integration: Authentication, data fetching, and error handling with external APIs
- Data Engineering: ETL pipeline design and implementation
- Python Development: Modular, maintainable code with proper documentation
- Data Analysis: Financial metrics calculation and statistical analysis using pandas
- Production-Ready Code: Error handling, logging, and performance optimization
The skills demonstrated in this project directly translate to professional contexts:
- Business Intelligence: Ability to create custom BI solutions that integrate with various data sources
- Financial Analysis: Experience with financial data modeling and visualization techniques
- Process Automation: Capability to build automated workflows that save time and reduce manual errors
- Data Integration: Expertise in connecting disparate systems through APIs and data pipelines
- API Security Best Practices: Implementation of secure authentication flows and credential management
- ETL Design Patterns: Architectural approaches for reliable data extraction and transformation
- Financial Data Modeling: Techniques for accurately representing and analyzing complex financial information
- Performance Optimization: Methods for handling large datasets efficiently while maintaining system responsiveness
- Documentation Excellence: Creating clear, comprehensive documentation that enhances code maintainability
The main dashboard provides a comprehensive view of financial health with key metrics and visualizations
Detailed transaction tracking with automatic categorization and filtering capabilities
Annual financial summary with trend analysis and year-over-year comparisons
Dedicated savings tracker with goal-setting functionality and progress visualization
This project demonstrates my ability to bridge financial analysis with modern data engineering practices — skills that I can apply to solve real business problems involving data integration, analysis, and reporting.