5G Paving the Way for Vast Data Volumes That Call for New Data Strategies and Management Platforms

The technological convergence between communications (5G) and distributed compute (edge clouds) is bound to be a driver of growth and change for the telecoms industry. A case in point is the manufacturing vertical where the yearly analytics and data services revenue is expected to reach US$82 billion by 2030, at a Compound Annual Growth Rate (CAGR) of 44%. The value at stake lies in the many data permutations that convergence enables and how that data is reused and reimagined. The bulk of data in many enterprise verticals remains dark, disparate and isolated.  There is, therefore, a need for parsing to mold the data into new forms and innovative products and to drive operational efficiency. Moreover, the adoption of cloud native methodologies at all levels of the stack calls for Mobile Service Providers (MSPs) to re-engineer their processes with a data centric-architecture as a building block, finds global tech market advisory firm ABI Research.

“The industry should view the convergence of IT and telecoms as a harbinger of a new age that amalgamates telco proprietary systems and modular Internet architectures,” says Don Alusha, Senior Analyst at ABI Research. “This hybrid environment calls for a 5G data governance system that rests on a (cloud) data management infrastructure anchored on two pillars: one, a standardized data format; and two, interoperability across multiple networks (e.g.,4G and 5G).  Furthermore, obtaining both structured data and unstructured data from the network and IT side respectively is a key requirement for the much-coveted data centric operations the industry is seeking.”

A key difference between 5G and pre-5G solutions is how to integrate the application at the service layer with data repositories. To that end, key vendors like Accedian, Nokia, Openwave Mobility, and TEOCO are already supporting Mobile Service Provider’s (MSPs) transition from an app-centric approach to a data-centric model akin to that found in webscale companies.  Those companies are not merely selling vast data repositories and analytics tools. The likes of Amazon, Cloudera, and Microsoft sell performance, scalability, and availability. In other words, they sell convenience at scale, a feat they can achieve by virtue of a harmonized and integrated technology, human capital, and the right organizational environment.

(MSPs) realize that the use of big data can lead to new data-driven services and use cases. For innovative use case to materialize, analytics processes must be pervasive and tap into a unified data lake, an area that, unlike web-scale players, operators have yet to fully exploit for monetization or operational efficiency. Further, a data strategy remains a key piece to the wider 5G cloud data management puzzle and one that AT&T and Telefonica are successfully leveraging. The wider MSP community must institute a broad analytics framework that factors in data standards to ensure they can correlate data, obtain business meaning, and give context to the services they are creating in a unified fashion.

“Vendors that provide 5G cloud data and traffic management solutions may consider establishing an ‘analytics environment’ as a symbiotic add-on to their big data platforms. Meaning an all-encompassing blueprint that guides MSPs toward the right culture and incentive systems that create and sustain the use of analytics tools (data layer and software tools). MSPs, on the other hand, must take on a process re-engineering undertaking where existing processes and associated functions are interwoven with the right data streams to successfully shift to a data-driven business and data-centric operations,” Alusha concludes.

These findings are from ABI Research’s 5G Cloud Data Management application analysis report. This report is part of the company’s 5G Core & Edge Networks research service, which includes research, data, and analyst insights.  Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.)

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