MarketWatch Aggregator
A multi-source data scraping platform aggregating financial market data from 15+ sources into unified dashboards with real-time updates, historical analysis, and trend predictions.
- Client
- MarketWatch Analytics
- Industry
- Analytics
- Type
- Data Scraping
- Year
- 2024
- Our role
- Backend
- Timeline
- 3 months
- Team
- 3 developers
Overview
MarketWatch Analytics' analysts spent 8+ hours daily gathering data from financial websites, consolidating into spreadsheets, and analyzing trends.
Process.
- Built scalable scraping architecture using Playwright for reliable browser automation.
- Created data pipeline with validation, aggregation, and storage.
- Built dashboard for visualization and analysis.
What we built.
- featReal-time scraping from 15+ financial sources
- featStock price tracking and historical data
- featMarket sentiment analysis from news sources
- featPortfolio performance tracking
- featSector and industry analysis
- featScheduled reports and email delivery
Hard parts.
fixFrequent site structure changes breaking scrapers
Built modular scrapers with multiple selector strategies (CSS, XPath, text matching), added automated failure detection with alerts, created fallback scrapers for critical data. Now recovers in <2 hours. Reliability improved to 96%.
fixData inconsistency across sources
Implemented data validation rules, created normalization pipeline, added source comparison logic, and documented source precision. Created data quality scores. Inconsistencies reduced to <0.1%.
fixStorage scaling issues
Implemented time-series database (InfluxDB) for efficient historical data, added data aggregation at hourly/daily levels, created materialized views for common queries. Query speed improved from 8s → 200ms.
fixReal-time update lag
Implemented WebSocket for live updates, added Redis cache layer for frequently accessed data, optimized scraping to run every 30 seconds for critical data. Update lag reduced to <2 seconds.
Built with
Node.js Playwright PostgreSQL Redis
Building something like this?
Tell us where the product is today. We reply within 12 hours.