Making Predictive Customer Support a Reality for Telcos

What this post added

This post details how telcos can leverage data streaming for predictive customer support, ingesting and processing real-time data from customer behavior and network performance to train predictive models for preemptive issue detection and resolution. It highlights the use of Confluent's platform for connecting, processing, and governing data streams to build live data products for AI/ML models, enabling proactive network health monitoring and issue resolution. Specific technical details include using Confluent Platform and Confluent Cloud with connectors for IBM MQ, Splunk, PostgreSQL, and SQL Server, cluster linking for hybrid/multicloud deployments, Apache Flink for stream processing to enrich data streams (e.g., joining call drop rates with network performance), and Stream Governance features like Stream Lineage, field-level encryption, RBAC, and Schema Registry. An example Flink SQL query is provided for identifying unhealthy network situations based on call success rates and clearing codes.