Tidy Transit: Real Life Data Modeling for Public Transportation
summary
Cal-ITP builds an open-source data warehouse that ingests GTFS schedules, GTFS realtime and EMV payments to unify 800 agencies (200 fixed‑route) and power monthly public quality reports and dashboards. Data pipeline uses Airflow, Kubernetes and BigQuery with analysis in Jupyter via siuba + BigQuery. Vehicle positions arrive GTFS realtime every 20s, EMV clears 2 days after, enabling fare‑capping, merchant reports and speed maps that find routes as slow as 5.5 mph and drive investment decisions.
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chapters (8)
- 0:00Introduction
- 3:20Cal-ITP mission
- 5:08Trip planning with real-time data
- 7:59Standardizing EMV payments
- 10:48Equity-focused fare discounts
- 11:33Data standards for transit analytics
- 14:02Speed analysis for transit investment
- 15:30Q&A
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