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Telecom Business Review | Wednesday, August 03, 2022
Telecom operators need to develop the internal skills necessary to fully utilize their data, whether by hiring more data scientists or upskilling existing staff.
FREMONT, CA: There are new opportunities for telcos to use machine learning (ML) and artificial intelligence (AI) due to the proliferation of sensors and executives' growing comfort with data-driven decision-making. While 99.9 percent of operators polled in a recent STL report desired to utilize these emerging technologies to improve network efficiency, operators were at varying stages of their data analytics journey, with the vast majority encountering obstacles.
Telecom operators must develop advanced analytics capabilities to create a solid base for future AI and ML skills.
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Network management: Network (resource) management, which includes network planning, deployment, maintenance, and the management of network capacity and resources, has been identified as one of the most significant opportunities—managing physical and virtual network infrastructure accounts for a significant portion of operators' capital and operational expenditures, which is not particularly surprising. Automation, advanced analytics, and AI (A3), especially advanced analytics, can significantly enable operators to leverage network insights and data to make more informed decisions regarding new network investments. Operators have also identified predictive maintenance as an important use case that will allow them to allocate resources to repair their networks more efficiently, thereby substantially reducing OpEx.
Service assurance: In the near future, advanced analytics (and eventually ML and AI) can also play a significant role in this important area. In the next, new service assurance products will be required to support an increasingly multi-vendor, disaggregated environment, new edge computing services, and maturing Internet of Things use cases. That is not to say that the value of advanced analytics is primarily in the "new" stuff. According to research, there is still unrealized value that can be derived from A3 in service assurance for 3G and 4G LTE, for instance, through more predictive algorithms. Advanced analytics in service assurance will pave the way for the future application of machine learning for more proactive root cause analysis.
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