Airline Operations (synthetic)

Business scenario

HA is an invented airline that runs a hub-and-spoke network from Dubai (DXB) to 28 destinations across the Middle East, Europe, Asia and Africa, plus a few point-to-point routes. The operations team wants to understand punctuality, how full the aircraft are and what each route earns.

Airports and distances use real public locations. Every flight, delay, passenger count and fare is generated by a script with a fixed seed, so the data is realistic in shape but does not describe any real airline.

Questions to answer with a dashboard

1. What is our on-time performance (arrival within 15 minutes) by route, month and aircraft type?
2. Which delay causes cost the most minutes, and how do they change by season?
3. Which routes have the highest and lowest load factor, and does that match revenue per flight?
4. How does fuel burned per passenger compare between aircraft types on long-haul routes?
5. Are cancellations concentrated on particular routes or months?

Tables, columns and data dictionary

dim_date

One row per calendar day. Mark it as the date table in Power BI and relate every fact table to date_key.

• date_key (integer): Day as a number, yyyymmdd (for example 20240229)
• date (date): Calendar date
• year (integer): Calendar year
• quarter (integer): Calendar quarter, 1 to 4
• month (integer): Month number, 1 to 12
• month_name (text): Month name in English
• day (integer): Day of the month
• day_name (text): Weekday name in English
• is_weekend (boolean): True for Saturday and Sunday

dim_airport

Airports served. Codes, names and coordinates are real public facts.

• airport_code (text): IATA airport code
• airport_name (text): Airport name
• city (text): City served
• country (text): Country
• latitude (decimal): Latitude in degrees
• longitude (decimal): Longitude in degrees

dim_aircraft

The airline fleet: one row per aircraft.

• aircraft_id (integer): Unique aircraft key
• registration (text): Invented registration code (not a real tail number)
• aircraft_type (text): Aircraft model
• seats (integer): Seats in the cabin configuration
• delivery_year (integer): Year the aircraft joined the fleet

dim_route

One row per direction of a route (DXB to LHR and LHR to DXB are two routes).

• route_id (integer): Unique route key
• origin_code (text): Departure airport
• destination_code (text): Arrival airport
• distance_km (integer): Great-circle distance
• scheduled_block_min (integer): Scheduled gate-to-gate time in minutes
• haul (text): Short (under 1,500 km), Medium (to 4,500 km) or Long haul

fact_flight

One row per scheduled flight. Cancelled flights have no passengers, revenue or delay figures.

• flight_id (integer): Unique flight key
• flight_number (text): Invented flight number such as HA512
• date_key (integer): Scheduled departure date
• route_id (integer): Route flown
• aircraft_id (integer): Aircraft used
• scheduled_departure (text): Scheduled departure time, HH:MM local
• status (text): Completed or Cancelled
• dep_delay_min (integer): Minutes late leaving the gate (0 if on time); empty when cancelled
• arr_delay_min (integer): Minutes late arriving (0 if on time); empty when cancelled
• delay_cause (text): Main cause when departure delay is 15 minutes or more; otherwise empty
• seats_available (integer): Seats offered for sale
• passengers (integer): Passengers carried
• load_factor (decimal): Passengers divided by seats available (0 to 1)
• revenue_usd (decimal): Ticket revenue for the flight in US dollars
• fuel_kg (integer): Fuel burned in kilograms

License and usage terms

Free to use (synthetic data)

You may use this synthetic data for learning, practice, demos, training material and portfolio projects, including in published reports. You may not resell the files themselves or present them as real data. The data is invented: it does not describe any real person, customer or company.