Telecom — Customer Knowledge Ontology Graph Creation Pipeline

Overview

The primary purpose of this DAG is to create ontology graphs that structure customer knowledge, thereby enhancing fraud and anomaly detection capabilities within the telecom industry. The process is triggered by the arrival of new customer data, which includes CRM data and results from Named Entity Recognition (NER) extractions. The ingestion pipeline begins with the collection of these data sources, followed by several processing steps. First, the system constructs initial graphs based on the c

The primary purpose of this DAG is to create ontology graphs that structure customer knowledge, thereby enhancing fraud and anomaly detection capabilities within the telecom industry. The process is triggered by the arrival of new customer data, which includes CRM data and results from Named Entity Recognition (NER) extractions. The ingestion pipeline begins with the collection of these data sources, followed by several processing steps. First, the system constructs initial graphs based on the customer data. Next, it integrates synonyms to enrich the graph structure, ensuring that variations in customer terminology are accounted for. Quality control measures are then applied to verify the integrity and accuracy of the graphs. Once validated, the graphs are stored in a graph management system, providing easy access through a query interface. Monitoring key performance indicators (KPIs) such as graph accuracy, processing time, and user query response time ensures the system operates efficiently. The business value of this DAG lies in its ability to provide a structured representation of customer knowledge, which can significantly enhance fraud detection mechanisms and improve overall decision-making processes in the telecom industry.

Part of the Fraud & Anomaly Analytics solution for the Telecom industry.

Use cases

• Improves accuracy in fraud detection processes
• Enhances customer understanding through structured data
• Reduces manual effort in data analysis
• Facilitates quick access to customer insights
• Increases operational efficiency in data handling