Telecom — Data Quality Assessment for Telecom Systems

Overview

The primary purpose of the Data Quality Assessment DAG is to evaluate the integrity and compliance of data within telecom systems. It ingests data from diverse sources such as customer databases, network performance logs, and billing systems. The ingestion pipeline is designed to handle large volumes of data efficiently, ensuring that the latest information is always available for analysis. Once the data is ingested, the pipeline applies a series of quality control tests, including validation ch

The primary purpose of the Data Quality Assessment DAG is to evaluate the integrity and compliance of data within telecom systems. It ingests data from diverse sources such as customer databases, network performance logs, and billing systems. The ingestion pipeline is designed to handle large volumes of data efficiently, ensuring that the latest information is always available for analysis. Once the data is ingested, the pipeline applies a series of quality control tests, including validation checks, completeness assessments, and consistency evaluations. These tests are crucial for identifying any anomalies or non-compliant data entries. The results of these quality assessments are then stored in a centralized quality registry, which serves as a comprehensive repository for data quality metrics. Additionally, the system generates alerts for any data that fails to meet predefined quality standards, enabling timely corrective actions. The DAG also incorporates recovery mechanisms to address detected anomalies, ensuring that data integrity is maintained. Key performance indicators (KPIs) are monitored throughout the process, including the percentage of compliant data, the number of alerts generated, and the time taken to resolve issues. By implementing this DAG, telecom organizations can significantly enhance their data quality management, ultimately leading to improved decision-making, regulatory compliance, and customer satisfaction.

Part of the Enterprise Search solution for the Telecom industry.

Use cases

• Ensures compliance with industry regulations and standards
• Enhances decision-making through reliable data insights
• Reduces operational risks associated with poor data quality
• Improves customer satisfaction by maintaining data integrity
• Facilitates proactive data management and anomaly resolution