Daily schedules for analysis, trend identification and driving strategic decisions.
We have partnered with Snowflake, the global leader in cloud data platforms, so we can expose our data directly to the customer via our new cloud-based platform. This gives you direct access to OAG’s worldwide airline schedules database and allows simple integration and configuration.
Key Benefits include:
Returning large queries in a matter of seconds and updated daily, this new delivery option removes lengthy processing and allows users access to raw data with their preferred analytical tool.
What data & functionality is available?
- Direct access to near real-time data means you can get value from the data faster.
- It is quick and easy to integrate with your analytical tool of choice e.g Tableau, Power BI to streamline your workflow.
- An intuitive user interface, simple to use and returns large queries in a matter of seconds.
Agility to configure the data for your specific needs.
- Reduced processing time and so reduced TCO – one customer saves > 8 hours of processing time per file.
- No need to extract data before using giving you more analysis time
- As volatility in the market continues, it gives you an aggregate view of what has changed in the schedule.
- Global Airline Schedule Data with full geographical coverage.
- Airline / Airport Specific Availability.
- Historical Views – Daily, Weekly, Quarterly.
- Changes and Withdrawn Flights.
New Premium Seats Data Now Available
- More granularity and accuracy of seats available at cabin level by flight, by cabin.
- Forward looking data will show 5 cabins available - First, Business, Economy, Premium Economy & Economy.
- Uses ML and FLAI (Flight AI Framework) data model combines historical, actual and scheduled data.
- Rigorous validation & quality assurance checks.
Recommended for those who need access to daily schedules for analysis, trend identification and driving strategic decisions.
- Key verticals such as Finance, Investment, Government and Consultants.
- Customers looking to significantly reduce data processing time and resource.
- Organisations who need to run queries against raw schedules data with fast returns.
Find out more: