Telecom — Telecom Data Quality Monitoring and Reporting System

Overview

The purpose of this DAG is to establish a robust monitoring system that ensures the quality of data and synthesized outputs in the telecom industry. By continuously collecting metrics on performance, errors, and user feedback, this workflow enables proactive management of data quality. The ingestion pipeline begins with the acquisition of data from various sources, including customer feedback logs, network performance metrics, and operational reports. Processing steps involve data validation, er

The purpose of this DAG is to establish a robust monitoring system that ensures the quality of data and synthesized outputs in the telecom industry. By continuously collecting metrics on performance, errors, and user feedback, this workflow enables proactive management of data quality. The ingestion pipeline begins with the acquisition of data from various sources, including customer feedback logs, network performance metrics, and operational reports. Processing steps involve data validation, error detection, and synthesis of quality metrics. Quality control mechanisms are integrated to ensure compliance with predefined KPIs, and alerts are triggered in case of any deviations. The outputs of this DAG include comprehensive dashboards for real-time monitoring, detailed audit reports for stakeholders, and alerts for immediate action. Key performance indicators such as data accuracy, error rates, and user satisfaction scores are monitored to evaluate the system's effectiveness. The business value lies in improved decision-making, enhanced customer satisfaction, and reduced operational risks through timely insights and actions.

Part of the Knowledge Portal & Ontologies solution for the Telecom industry.

Use cases

• Enhanced data accuracy leading to better decision-making
• Proactive identification of issues before they escalate
• Improved customer satisfaction through quality assurance
• Streamlined reporting processes for stakeholders
• Reduction in operational risks via timely insights