A Leading Airline Accelerates Forecasting Process by 22X
A Leading Airline Case Study
This airline is one of the largest airlines in the world, with thousands of flights per day to hundreds of destinations in more than 50 countries, serving around a million passengers each day.
This airline needed to leverage mass amounts of data from the served airports to optimize logistics concerning resources, fight plans, crews, etc. – especially upon unplanned changes,for rapid accurate response. They required to ingest real-time data from multiple applications and data sources and analyze the data to optimize operations and pricing.
- Ingest ~billion flight records in minutes rather than hours
- Ability to query data from multiple airports in real-time at low latency
- Ability to update with low latency many airports to adjust forecast and influence
- Event-driven architecture
- Cloud nativeness
With GigaSpaces’ in-memory real-time analytics platform, this customer was able to predict and instantly handle any change in the scheduling and operating workflow. The platform’s event triggers analytics and machine learning and leverages data ingested and aggregated such as fuel costs, weather, news and more. The ability to access historical data, such as past delays during peak traffic, enriches the insights gleaned and increases the accuracy of the delay probability.
- Speed and Agility: Reduced forecasting ingestion from 3 hours to 8 minutes
- Live interactive querying and analytics through Spark SQL < 150ms latency