Ravi Chalaka

Enhancing Telecom Services with Real Time and Historical Data Analytics

Blog Post created by Ravi Chalaka on May 28, 2015

The telecom landscape is undergoing rapid change with 7 billion mobile subscribers globally today, most with a fast growing appetite for voice, data and video communication and related services. These changes can challenge even the largest and the strongest network providers by over taxing the capacity, availability,  security, and the high-speed delivery of services and data.  An inability to keep up with customer requirements can jeopardize those valuable relationships.

 

At the same time, 78% of all households in the developed world have Internet access and 25 billion devices such as machines, cars, sensors, cameras, etc. known as the Internet of Things (IoT) are connected.  The result is more devices, more subscribers, and more data that requires more efficient use of network bandwidth.

 

The Big Data revolution is having a huge impact on telecom providers as a result. Telco operators collect millions of network data measurements across their network each second; for example AT&T reported 30 billion measurements collected per hour! Regrettably, most of this data goes untapped due to inadequate solutions to extrapolate the value in real time or to correlate it to past trends for predictive insight.  A major challenge for telecom is in granular network performance that is monitored in real-time to predict and mange traffic congestion. In addition to internal telecom business and operations data, the sources of data are wide ranging: consumer (usage, social, location…), enterprise, industrial (including growing IoT and M2M data).Telecom providers also have an opportunity to leverage this wide range of data to offer new services to attract and retain customers, plus optimize the use of personnel and network resources to increase profitability.

 

To meet these demands and control costs, telecom  service providers and their major users (such as financial services and internet services) need sophisticated ways to assess the efficiency and security of their networks.  These companies are looking for answers now. A recent Heavy Reading Survey showed that 87% of operators view big data / advanced analytics as “critical” or “very important” to their company in the next 12-24 months and 42% of Operators Plan to Implement Advanced Telecom Analytics in 2015 (Heavy Reading survey).

 

Hitachi Data Systems introduced Live Insight™ for Telecom solution to enable providers to generate new revenue, reduce costs or improve service with real time, predictive big data analysis. Hitachi Live Insight for Telecom  enables service providers to offer customers smarter, more dependable services with a higher quality of experience. This solution is unique in how it applies intelligent machine learning and predictive analytics to both real-time and historical data in parallel, to improve network performance before problems occur. It provides for simultaneous ingest and analysis of up to one million events per second per processing engine with millisecond level visibility. This represents a vast improvement over the current 1-5 minute industry norm. Live Insight for Telecom has been optimized to achieve cost efficiency without compromising carrier-class and is based on an open architecture to ensure the flexibility for developing differentiated applications for operations, business and carrier-hosted user cases.

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