SWIM Training & Workshop

“The ATM community will depend extensively on the provision of timely, relevant, accurate, accredited and quality-assured information to collaborate and make informed decisions.”

ICAO DOC 9854 – Global ATM Operational Concept (GATMOC)

In this customisable training course, Snowflake Software will cover everything about SWIM, from why it is needed and how it can be implemented through to the individual standardised data-exchange models and protocols. Most importantly, the course addresses how SWIM will impact your organisation, systems and customers. As experts in Data Management within Aviation for over 10 years, the Snowflake Software team have worked with many organisations on their implementation of System Wide Information Management.

Classroom courses are available in house or in the Snowflake Software HQ. There will be plenty of opportunity for Q&A. Materials including hardcopies of course slides, notes and useful references will all be provided.

Who could benefit the most from this course:

Stakeholders from organisations looking to transition to SWIM, such as people working within the AIM departments of ANSPs.

Certificate awarded
All candidates will receive a certificate of attendance after the course.
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COURSES

USE-CASE

In the SWIM in ASEAN Demonstration 2019, Snowflake Software’s Flight Object Manager formed part of the architecture showcasing the operational benefits of implementing SWIM. Distributing meteorological and flight information via SWIM ensures all stakeholders have the same situational awareness necessary for collaborative decision making. In this example, the severe turbulence SIGMET from the meteorological office is shared early via SWIM with the airspace users and airspace operators. Timely information sharing enables strategic planning, minimising the impact of disruption. In this case, the result of the strategic decision is an in-flight trajectory re-route to avoid the turbulence. When interfaced with A-CDM and ATFM systems, the continuous trajectory updates lead to improved demand/capacity balancing, flow management, and predictability. Speak to our team for more information on this scenario and other operational examples explored during the trial.