Evaluating Metadata For Governance, Stewardship And Quality Control Architecture In Telecom Data Mining

Abstract

The telecom sector is focused on data mining to stimulate innovations, operations, and ways to improve customer experiences. Nevertheless, the efficiency of the processes is preconditioned by the presence of the sound metadata management that guarantees the accuracy, consistency, and reliability of data. In the study, the focal aspect is testing and validation of metadata in the governance, stewardship and quality control architecture in the telecom data mining systems. An end-to-end model is introduced to measure the integrity of metadata that includes automatic tools of testing policies, utilization of rules that validate data, and stewardship approaches. Considering the peculiarities of telecom sector, including large amounts of data, changing schema, legislation, the framework guarantees it will fit with industry specifications, and business objectives. Implementation case studies reveal the benefits of improvements of metadata quality, data governance efficiency, and other aspects of system performance. The results give important perspectives on creating metadata management industry-specific industry solutions at scale, on confidence generation in the telecoms data environs, and on improving data-driven decisions.

In contemporary telecom networks, the issue of data management and how it is administered is important performance and operational efficiency of telecom networks. The current paper deals with the testing and validation of a metadata-driven architecture that should be used to promote the sound data stewardship in telecom environments. The suggested architecture will use metadata to automate such important data governance activities as data lineage monitoring, quality, and policy enforcement. The architecture testing Methodology that determines the architecture performance by testing it under the normal or standard telecom networks environment and scenarios of high data speed and data heterogeneity. The validation also occurs with concrete examples of its usage, presenting the architecture to improve the quality of data, simplify the work and guarantee compliance with the regulations of the industry.

The results provide great lessons to telecom organizations to consider metadata mining approaches that favor the regulatory framework, operational requirements, and innovation aspirations. Because the study reveals the central importance of architectural design, it can play the role of contributing to the development of successful strategies to achieve optimal data governance and quality in the telecom sector. Findings confirm the suitability of metadata-based approach in managing the challenges of telecom data ecologies as well as facilitating flexibility to changing operational and regulatory needs. The present work has given the telecom stakeholders the structure of bringing and validating metadata-based solutions and forwarding the advances in best practices of data stewardship in their industry. The findings help to prepare right practices and scalable metadata governance and metadata quality control to form trust and efficiency in data management processes by responding to peculiarities of telecom data ecosystems.