Big Data Analytics for Enhanced In-Flight Internet Performance: A Gogo Case Study

The migration to AWS cloud not only expanded the data processing capacity but also saved Gogo costs spent on licenses and the on-premise infrastructure. The cloud-based unified data platform collects and aggregates both structured and unstructured data, providing a comprehensive view of the system's performance. The application of data science models for predicting antenna equipment failure and reducing the NFF rate has significantly improved the reliability of the in-flight internet service. The comprehensive reports provided to Gogo's C-level decision-makers have enabled them to make informed decisions based on data. The reporting tool developed has been instrumental in identifying user pain-points during the first fifteen seconds of the Internet connection, thereby improving the user experience.

Migration to the cloud reduced costs on licenses (Cloudera/Microsoft) and on-premises servers.

The no-fault-found rate was reduced by 75%, saving costs on unnecessary removal of equipment for servicing.

Predictive analytics allows predicting the failure of antennas (>90 %, 20-30 days in advance).