Service Providers, Enterprise Services, Service Provider Tec...
By Paul Bremner 20 Aug 2020
With the almost universal penetration and use of mobile broadband, telecom operators are finding that their networks and operations are generating more data, at faster rates, than ever before. In turn, consumption of digital services places demands on operators to deliver high-quality customer experiences. Exploiting live streams of data to derive insights that enable immediate and correct responses has become critical for telecoms application providers. However, one of the biggest challenges lies not in simply collecting the data, but correlating and analyzing it in real time to proactively respond to situations that present revenue opportunities or impact a subscriber's experience. Telecom operators and application vendors alike must understand how these live streams of data can be harnessed effectively using existing and upcoming technologies.
The telecommunications industry is facing multiple challenges; revenues are declining, yet traffic is growing exponentially while competition is intensifying among peers and over-the-top (OTT) service providers. While operators have adopted several strategies to deliver and monetize new services, as well as transform existing operations and network infrastructure, they must do a better job of harnessing insights generated from live, real-time data streams.
While much has been said about big data (historical stored data generated across the business), there is also significant potential that can be derived from the analysis of fast data. First, real-time analytics will enable operators to deliver the personalized service their digital subscribers expect. Second, operator applications can deliver proactive capabilities that use insights based on the current context of each subscriber and the services they consume, opening the way for responses such as targeted offers or delivery of just-in-time care to subscribers.
Traditional business intelligence (BI) and data warehousing approaches that rely on stored data and bulk analysis are incapable of delivering timely insights. Conversely, fast data technologies can enable the processing of live streaming data to drive immediate, actionable, and effective business results. Real-time analytics, using fast data technologies, is becoming essential for operators who are embracing innovations such as software-defined networking (SDN) and network functions virtualization (NFV) to support rollout of new services such as Internet of Things (IoT) and machine-to-machine (M2M) communications.
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