Open Source Solution using Data Pipeline Architecture for Telco Big Data Analytics

Abstract

Customer churn has emerged to be one of the greatest challenges in the rapidly changing sector of telecommunications. To avert customer churn proactively, this thesis explores employing an open-source data pipeline architecture particularly for big data analytics to predict churn in real time. The theoretical underpinnings are allied with practical use cases, specifically, developing and implementing a set of machine learning models towards accurate churn prediction. newline