Mahmood Jawad Abu-AlShaeer

Background: Telecommunications has been rapidly moving from legacy systems to highly flexible modern architectures to accommodate the expanding demand on its services. This evolution is critical in providing the capacity needed for new technologies like 5G, IoT, and applications powered by AI. Objective: The study aims at establishing a literature review on the evolution from the more or less obsolete telecommunication structures to new generation digital structures, opportunity factors, technologies that facilitate this change as well as the value addition by this evolution. Methods: The literature review was followed by an examination of industry case studies of 50 telecommunications firms across the globe. The study looked at best practices including network resource utilization, operational price, and service delivery effectiveness, pre and post implementation of technologies like software-defined networking (SDN), network function virtualization (NFV), and cloud-native architectural strategies. Results: The analyses brought out the fact that with the new architectures, network scale up capabilities were enhanced by 70%, operation costs were brought down by up to 30% and service delivery rates were boosted by 40%. Nonetheless, 85% of the firms that implemented the software upgrade faced issues with system integration, which took fifteen months on average before the new system was fully incorporated, and the firms incurred an additional 20% in implementation costs in accommodating integration issues. Conclusion: Extension of telecommunication architectures towards digital landscape improves performance, capacity, and affordability thereby allowing the providers to address next generation applications. However, while making this transition, there are a number of risks that organizations have to face and it is very important to manage them in order to have maximum benefits from using new digital technologies.

Background: The telecommunication industry is currently witnessing an unparalleled growth in traffic data with a concomitant growth in the complexity of networks. As operators seek to achieve high availability of the networks, it is almost compulsory to employ the BDA for improved quality of service and increased operational performance. Objective: The study aims to provide a systematic review of the deployment of BDA in enhancing the primary characteristic indicators of telecommunications networks, to include availability of upgraded latency and throughput levels and network dependability. Methods: The research method used was summed up by quantitative analyses of the key performance parameters of the networks, along with the qualitative results of case studies conducted with major telecommunications operators. Information was collected from multiple networks as well as analyzed with the use of machine learning to be able to predict possible performance issues. Results: The study demonstrates that there is the possibility for reducing latency utilizing BDA with enhancements of up to 40%. In addition, the throughput has been raised by an average of 30% and the predictable analytics lead to 25% reducing in network downtime to improve the reliability and satisfaction of the user experience. Conclusion: The information provided in this study highlights the importance of Big Data Analytics for the telecommunication industry, proving that the proper integration can bring tangible improvements to the existing networks. One future development that constitutes the need for innovative analytical technologies is the rise in data traffic and sophisticated network requirements.