Airline bookings & delays
=========================

Domestic flights between 24 real Indian airports on eight fictional airlines: scheduled and actual departures, delays and their causes, and passenger bookings with fares. Fog delays pile up at northern airports in December and January; fares climb as departure approaches and around festivals.

Category: Travel
Licence: CC0-1.0
Synthetic data generated by DataStride. Airports, places and seasons are real; airlines, flights and passengers are fictional.
Build: 940aea8e3b2c8169

air_airports (24 rows)
  airport_code           VARCHAR(3)     [key] IATA code.
  city                   VARCHAR(40)    City served.
  state                  VARCHAR(40)    State.
  is_north               INTEGER        1 for airports in the winter-fog belt.

air_airlines (8 rows)
  airline_code           VARCHAR(2)     [key] Airline code (fictional).
  airline_name           VARCHAR(40)    Airline (fictional).
  model                  VARCHAR(20)    Low-cost, full service or regional.

air_flights (2000 rows)
  flight_id              INTEGER        [key] Flight identifier.
  airline_code           VARCHAR(2)     -> air_airlines.airline_code Operating airline.
  origin                 VARCHAR(3)     -> air_airports.airport_code Departure airport.
  destination            VARCHAR(3)     -> air_airports.airport_code Arrival airport.
  flight_date            DATE           Scheduled departure date.
  scheduled_dep          TIMESTAMP      Scheduled departure, local time.
  delay_minutes          INTEGER        Departure delay in minutes; negative is early; null means cancelled.
  delay_cause            VARCHAR(30)    Main cause for delays of 15 minutes or more.
  seats                  INTEGER        Seats on the aircraft.

air_bookings (5000 rows)
  booking_id             INTEGER        [key] Booking identifier.
  flight_id              INTEGER        -> air_flights.flight_id Flight booked.
  passenger_name         VARCHAR(80)    Passenger (fictional).
  booked_on              DATE           When the ticket was bought.
  cabin                  VARCHAR(10)    Cabin.
  fare                   DECIMAL(10,2)  Fare paid, INR. Rises as departure nears.
  channel                VARCHAR(12)    Where it was sold.
  status                 VARCHAR(12)    Outcome for the passenger.

Deliberate data-quality quirks (clean them before you aggregate):
  air_bookings.channel: mixed case
