Flight Ticket Meta Search & Analysis
Big-data internship project at Suncaper Data (State Information Center base) — collected, cleaned and analysed large-scale flight-ticket datasets to surface pricing & demand insights for stakeholders.
Industry-rated big-data internship project completed at Chengdu Suncaper Data — the Big Data Innovation & Entrepreneurship Base of the State Information Center.
I owned the end-to-end pipeline: collecting raw flight-ticket data from multiple sources, cleaning and normalising it into a unified schema, then running price-trend, route-popularity and seasonal-demand analyses to surface insights stakeholders could act on.
The project was awarded an overall evaluation of Excellent — the highest grade given to interns on that programme.
Multi-source data collection
Reliable scrapers and importers across multiple ticketing data sources, with retry logic and rate-limit handling.
Cleaning & normalisation
Pandas-based ETL pipeline that deduplicates, enriches and validates records before they hit the analysis layer.
Pricing & demand analytics
Trend analysis on routes, seasons and price elasticity — packaged as charts that non-technical stakeholders can read in seconds.
- Awarded an overall Excellent evaluation by the supervising team
- Processed and cleaned millions of flight-ticket records into a single analytics-ready table
- Surfaced pricing & demand insights through clear, decision-ready dashboards