Jelena is a data scientist currently employed in Swisscom’s Data, Analytics and AI department. She finished her Computer Science master studies at EPFL and joined Swisscom firstly as an intern, and then as a full-time employee. Jelena has always enjoyed trying to make complex problems understandable to different audiences. She achieved this by working as a teaching assistant, by developing and promoting innovative topics like the Hyperloop, and encouraging younger generations of talents through initiatives like GirlsCoding. These days, in addition to improving the anomaly detection models for business process monitoring, Jelena is trying to make data science tools useful and accessible to various stakeholders.
Talk: Business Process Monitoring with Anomaly Detection in Practice
DevOps teams within Swisscom are responsible for ensuring that any issues that could affect users are quickly addressed. This quest is challenging due to the high volume of available metrics, events, and traces (~300GB daily).
We will show how we designed and deployed an anomaly detection system based on Prophet models, PySpark, and MLflow, which analyses performance, throughput, and error metrics of important business processes. These analytics are displayed in an end-to-end monitoring tool which provides a holistic view of many distributed systems and gives actionable insights to the teams.