Schedule: Telecom sessions

Tim McKenzie examines why planning 5G network rollout and associated services requires a good understanding of location-based data. Accurate addressing and linking consumers to property or points of interest allows data enrichment with attributes, demographics and social data. Companies use location to organize and analyze network and customer data to understand where to target new services. Read more.

As a fintech company of China Telecom with half of a billion registered users and 41 million monthly active users, risk control decision deployment has been critical to its success. Weisheng Xie and Jia Zhai explore how the company leverages Apache Pulsar to boost the efficiency of its risk control decision development for combating financial frauds of over 50 million transactions a day. Read more.

T-Mobile successfully improved the quality of voice calling by analyzing crowdsourced big data from mobile devices. Alex Yoon walks you through how engineers from multiple backgrounds collaborated to achieve 10% improvement in voice quality and why the analysis of big data was the key to the success in bringing a better voice call service quality to millions of end users. Read more.

Heitor Murilo Gomes and Albert Bifet introduce you to a machine learning pipeline for streaming data using the streamDM framework. You'll also learn how to use streamDM for supervised and unsupervised learning tasks, see examples of online preprocessing methods, and discover how to expand the framework by adding new learning algorithms or preprocessing methods. Read more.

Jonghyok Lee Chon Yong Lee discuss T-CORE, SK Telecom’s monitoring and service analytics platform, which collects system and application data from several thousand servers and applications and provides a 3D visualization of the real-time status of the whole network. Join in to hear lessons learned during development. Read more.