In this post, we will be discussing the challenges of Big Data in the Telecommunications Industry, including Volume, Variety, Complexity, and Velocity.
- Volume: With the rise of 5G mobile networks, operational data generated from each call or session is increasing dramatically. The addition of GPS, location-based services, and social media is adding to this deluge of data. With the implementation of IPv6, there will be as many IP addresses as there are grains of sand on Earth, enabling a significant increase in the number of Internet-connected devices. 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.
- Variety: Social media, mobile devices, and sensors that monitor everything from utility use to medical compliance are flooding telco infrastructures with data in a wide range of 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.
- Complexity: Telcos must integrate legacy operational and business systems that still have useful life with new environments. They must support batch to real-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 that are too large and complex for human response. And all of this must be done while ensuring data quality and accessibility across multiple solutions for regulatory compliance.
- Velocity: Velocity refers to the rate of data generation. Traditional data analytics are 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. For example, data generated through mobile apps, such as demographics, geographical location, and transaction history, can be used in real-time to offer personalized services to customers, which would help retain customers and increase service level.
E-SPIN Group has been in the business of supplying, consulting, managing, training and maintaining enterprise ICT solutions for multinational corporations and government agencies in the region since 2005. If you have any requirements or project inquiries, please don’t hesitate to contact E-SPIN. You may also be interested in other posts.
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The post original create 2017-Nov-7, rewrite and last update 2023-Jan-09.