The Challenge
The business team needed a way to monitor key metrics in real-time without relying on slow, manually-generated reports. They needed interactive visualizations that could handle large datasets efficiently.
My Role
As Senior Frontend Engineer, I:
- Designed the frontend architecture
- Implemented complex data visualizations
- Optimized rendering performance
- Integrated real-time data streams
Technical Approach
Data Visualization
We used D3.js for custom visualizations:
- Time series charts with zoom and pan
- Interactive heatmaps
- Customizable pie and bar charts
- Geographic data maps
Real-Time Updates
WebSocket integration for live data:
- Efficient diff-based updates
- Reconnection handling
- Optimistic UI updates
- Fallback to polling
Performance Optimizations
Handling millions of data points required:
- Data aggregation on the server
- Virtualized lists and tables
- Canvas rendering for dense visualizations
- Web Workers for heavy computations
Key Features
- Customizable Dashboards - Drag-and-drop widget placement
- Advanced Filtering - Multi-dimensional data filtering
- Export Capabilities - PDF and CSV exports
- Alerting - Configurable threshold alerts
- Sharing - Shareable dashboard links
Results
- Processes 10M+ data points daily
- Under 100ms latency for real-time updates
- 4.8/5 user satisfaction score
- 80% reduction in time to insights