ECommerce Analytics Dashboard
Project Overview
The ECommerce Analytics Dashboard is a comprehensive business intelligence solution built on Google Cloud Platform for a fintech firm. This end-to-end data analytics platform processes loan data, optimizes query performance, and delivers actionable insights through interactive dashboards, significantly improving risk oversight and reporting workflows.
Key Features
☁️ Google Cloud Platform Integration
- BigQuery Integration: Advanced SQL queries for loan data processing and analysis
- Cloud Storage: Efficient data storage and retrieval for large datasets
- Scalable Architecture: Cloud-native solution designed for enterprise-level data processing
📊 Advanced Data Processing
- SQL Optimization: Created “CTAS” (Create Table As Select) tables for optimal query performance
- Data Transformation: Integrated and transformed loan data from multiple sources
- Performance Tuning: Streamlined reporting workflows with optimized database queries
📈 Interactive Business Intelligence
- Looker Dashboards: Built comprehensive dashboards for key financial metrics
- Cross-Filtering: Advanced filtering capabilities for detailed data exploration
- Automated Refresh: Real-time data updates and automated report generation
- Conditional Formatting: Visual indicators for risk trends and loan status monitoring
🎯 Stakeholder-Focused Design
- User-Friendly Interface: Intuitive dashboards designed for non-technical stakeholders
- Risk Monitoring: Key metrics tracking for loan status and risk assessment
- Operational Insights: Actionable data for improving business processes
Technical Implementation
Cloud Technologies
- Google BigQuery: Data warehouse and analytics engine
- Google Cloud Storage: Scalable object storage for data files
- Looker: Business intelligence and data visualization platform
- Google Cloud Platform: Complete cloud infrastructure
Data Processing
- Advanced SQL: Complex queries for data transformation and analysis
- CTAS Tables: Optimized table creation for improved query performance
- Data Pipeline: Automated data processing and transformation workflows
Analytics & Visualization
- Interactive Dashboards: Real-time business intelligence dashboards
- Cross-Filtering: Advanced data exploration capabilities
- Conditional Formatting: Visual risk indicators and status monitoring
- Automated Reporting: Scheduled report generation and distribution
Business Impact
Operational Improvements
- Enhanced Risk Oversight: Improved monitoring of loan status and risk trends
- Scalable Reporting: Streamlined workflows for financial loan department
- Data-Driven Decisions: Actionable insights for business strategy and operations
Technical Achievements
- Performance Optimization: Significantly improved query performance through CTAS tables
- Automation: Reduced manual reporting effort through automated workflows
- Scalability: Built solution capable of handling enterprise-level data volumes
Project Metrics
- Data Sources: Multiple loan data sources integrated and processed
- Query Performance: Optimized through advanced SQL techniques and CTAS tables
- Dashboard Features: Cross-filtering, automated refresh, and conditional formatting
- Stakeholder Adoption: Successfully deployed for financial loan department use
Live Demo
Analytics Dashboard: https://kkebaara.github.io/DataAnalystPortfolio/index.html
Technical Skills Demonstrated
- Google Cloud Platform: BigQuery, Cloud Storage, and cloud architecture
- Advanced SQL: Complex queries, CTAS tables, and performance optimization
- Business Intelligence: Looker dashboard development and data visualization
- Data Analytics: End-to-end data processing and transformation workflows
- FinTech Solutions: Specialized knowledge in financial data and risk management
Future Enhancements
- Machine Learning Integration: Predictive analytics for loan risk assessment
- Real-time Processing: Stream processing for live data updates
- Advanced Visualizations: Custom charts and interactive data exploration
- API Integration: RESTful APIs for external system integration