Near Real–Time Call Detail Record ETL Flows

Abstract

Telecommunication companies face significant business challenges as they strive to reduce subscriber churn and increase average revenue per user (ARPU) by offering new services and incorporating new functionality into existing services. The increased number of service offerings and available functionality result in an ever growing volume of call detail records (CDRs). For many services (e.g., pre-paid), CDRs need to be processed and analyzed in near real-time for several reasons, including charging, on-line subscriber access to their accounts, and analytics for predicting subscriber usage and preventing fraudulent activity. In this paper, we describe the challenges associated with near real-time extract, transform, and load (ETL) of CDR data warehouse flows for supporting both the operational and business intelligence needs of telecommunication services, and we present our approach to addressing these challenges.