Telecom operators are in a very particular position, managing critical, complex infrastructure while having to deal with decreasing core-business profit margins. The role of operators is crucial for providing access to the digital world, and for this reason service availability guarantees are often enforced contractually (SLAs).

To ensure operational excellence, it has become common practice for Telcos to leverage infrastructure usage data. These data are collected in addition to data that most businesses collect about customer interaction and business processes. Thus, operators find themselves processing large amounts of data, which can naturally drive them to develop Data Science and Machine Learning expertise.

In this track we want to dive into specific approaches of various operators when it comes to using the rich data available and adopting ML techniques in a consistent fashion.

The topics we envision are:

• Leveraging infrastructure measurements and usage data to improve availability, detect anomalies, and automate operations.
• Extracting additional value from network usage data, e.g., aggregated mobility indicators and CO2 emission estimation.
• Addressing data privacy, ethics, and compliance.
• Improving customer experience via customer understanding.
• Enhancing customer interaction though conversational AI.