With 4G providing the fire power, data volumes are exploding across the mobile environment, and communications service providers (CPSs) are in danger of being overwhelmed by the assault of Big Data on their often struggling networks. The onslaught of data already has reached the point at which one operator reports receiving and interpreting 40 billion records a day, estimating that volumes will rise to 100 billion by the end of this year. Moreover, research firm IDC predicts that, by 2020, digital data will swell by a factor of 300.
Such enormous amounts of data can be daunting if we mistakenly think of them in the same way we consider a continuous blast of water from a fire hose. Since every drop of water in the stream is pretty much the same as all the others, we find no benefit in analyzing the content of the blast; our tendency is simply to try to restrict it in some way. Telecommunications data, however, is not composed of molecules, but of messages. Every single element of the stream is different and can offer immense marketing insight into consumers’ thinking, preferences and intentions. In addition to battling the stream, CSPs should be looking for ways to welcome the arrival of all this information and mining it for the benefit of subscribers and providers alike.
Conversely, doing nothing with the data that barrels through the network means operators will spend increasing amounts of time and budget to store data without any immediate offsetting benefit. Using the data as an asset, however, can have tremendous value.
The first step toward understanding and using all of this data, commonly referred to as Big Data, is for CSPs to equip themselves with diagnostic tools and solutions that allow them to view and manage their telecoms landscape in four segments:
- Subscriber behavior: Operators have at their fingertips a potential goldmine of personal data relating to presence, location and preference. Networks should focus on this multi-dimensional information related to subscribers’ interactions with the services and applications they use.
- Services and apps: With deep packet classification, CSPs can see each of the unique services that go across their mobile broadband network for each customer. This capability makes it possible to spot traffic issues and real-time state-of-play data, helping identify, predict, alert and isolate problems as they occur.
- Technologies used: The mobile environment is evolving so that services are becoming more integrated, fragmented and often beyond the control of operators. Therefore, providers who want to successfully manage new technologies, protocols and devices need analytics across both legacy and next-generation technologies.
- Network performance: Network components are becoming functionally more complex, with a need to serve multiple technologies, through a variety of vendors and standards. The key to efficiency is in ensuring that the network maintains a 100% run rate. Core network applications are available that reduce outages, accelerate resolution time frames and improve network quality. These applications can be managed by one end-to-end system.
With such a comprehensive outlook, operators gain the network intelligence required to see more than simply the data that flows through the pipe; they can learn its sources, destinations, intent and purposes. That knowledge imparts real meaning and value to the data.
The data will not analyze itself, however it must be heeded, correlated, located and contextualized. Operators must realize that merely attempting to sort out indicative trends through macro-level information is not enough if they expect to fully interpret and monetize available data. Rather, they must approach the data on a micro level and assess it through the lens of the four segments listed above.
This methodology means CSPs never miss an opportunity because of events occurring in parts of the network that they could not see. Additionally, it brings new capability to the telecoms model, offering the same agility as that of OTT players.
Full visibility into the network is derived from real-time, end-to-end data collection and analysis that exposes hidden issues while providing unparalleled breadth and depth of insight.
The good news is that the technology to do this already exists and can be implemented with the help of a telecoms intelligence provider. Technology for the four-dimension world of valued data allows operators to follow and analyze every path of the data journey, creating the survival strategy for the modern age and a competitive advantage in the LTE environment. Without it, the heightened demands of LTE will drive glitches to become inefficiencies, leading to complaints and time-consuming drains on resources, ultimately generating churn and lost opportunities for revenue.
One source of guidance is available from Tektronix Communications in the form of a comprehensive set of new best practices for the telecoms industry and covering Big Data analytics implementation. This resource includes a reference model—a roadmap and how-to guide to deal with Big Data analytics—and a detailed set of business use cases showing a variety of ways for operators to extract value from Big Data. Whitepaper: Explore Telecom Intelligence in 4 Dimensions
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