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Google Cloud and DigitalRoute announce a collaboration to solve data readiness challenges for AI-driven autonomous network operations in telecommunications.
•Raw telecom data faces four key barriers: format disparity (ASN.1, XML, Binary), massive 5G volume/velocity, schema evolution from upgrades, and correlation complexity across network elements.
•DigitalRoute's Usage Engine runs on Google Kubernetes Engine (GKE) to normalize and decode complex binary messages into a unified common data model, filtering noise before storage.
•A dual-path strategy routes real-time data to Spanner for network digital twin construction and historical data to BigQuery for long-term analytics and Vertex AI model training.
•NSTA (Network and Subscriber Trace Analysis) aligns messages from different nodes by timestamps and identifiers to build coherent session flows for AI agents.
•The architecture enables anomaly detection, automated root cause analysis correlating RAN with core trace data, and predic
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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