Big Data Challenges for Telecommunications Provider
With the advent of LTE/4G mobile networks, the volume of operational data generated with every call or session is increasing tenfold. The expanded use of GPS, location-based services, and social media is adding to the torrent of data. Finally, the advent of IPv6 will create as many IP addresses as there are grains of sand on Earth, allowing the number of Internet-connected devices to grow exponentially.This volume of data requires new real-time operational capabilities for functions such as real-time charging and event-based marketing—and that in turn demands increased data storage for compliance and potential future uses as well as new tools for mediating, managing, and archiving data within available time frames.
Social media, mobile devices, and sensors that monitor everything from utility use to medical compliance are flooding telco infrastructures with data in myriad formats. Telcos must enrich their CDR data with location-based services, financial information, and other unstructured data, then standardize it for business intelligence platforms before they can analyze it for greater subscriber insight and new business opportunities.
Telcos must integrate legacy operational and business systems that still contain years of useful life with new environments. They must support batch to right time data to enable applications such as real-time CRM while also delivering their own cloud based services and support from other vendors. They also need complex event processing systems that can handle data volumes too large and complex for human response. And all this must be done while ensuring data quality and accessibility across multiple solutions for regulatory compliance.
Velocity refers to the rate of generation of data. Traditional data analytic is based on periodic updates- daily, weekly or monthly. With the increasing rate of data generation, big data should be processed and analyzed in real- or near real-time to make informed decisions. The data generated through Mobile apps, for instance, demographics, geographical location, and transaction history, can be used in real-time to offer personalized services to the customers. This would help to retain the customers as well as increase the service level.
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