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CSPs must revisit the data layer of their networks to capture 5G opportunity: A Q&A with Volt Active Data

‘There is an important confluence of IT data and OT data that is going to drive the SLAs [service-level agreements] and services provided by CSPs,’ says Volt Active Data exec

According to Dheeraj Remella, the chief product officer at Volt Active Data, 5G stands out from pervious generations of cellular technologies by delivering both an increase in speed and a “new belle of the ball” in the form of lower latency. This, he continued, opens up new monetization opportunities for communications services providers (CSPs), particularly for enterprises, as long as they carefully pair technology investments to desired business outcomes. 

But, figuring out how to offer new services and enabling new use cases that take advantage of 5G is only one piece of the monetization puzzle.

In a Q&A with RCR Wireless News, VRemella explains that if CSPs want to support 5G-enabled enterprises, they need to evolve their internal business and operation systems, as well.

Q: What role do data platforms play in 5G monetization? How have they had to evolve to support the applications being enabled by 5G?

A: 5G networks are software driven end-to-end. This is done consciously to allow CSPs to be agile in their ability to provision and bring to market new products. When all layers are software driven, the entire system is producing data to inform and decide. This means that it is not just the subscriber data that is of interest, but rather data about the network is also important. 

There is an important confluence of IT data and OT data that is going to drive the SLAs [service-level agreements] and services provided by CSPs. When splitting the world into things to do to enable 5G and the things to do enabled by 5G, CSPs internal systems on both the business and the operations side need to evolve to support the 5G-enabled enterprises and industries. This means that most of the processes that used to be cyclical will need to become continuous. To tie into the technical elements, things that were based on periodic and batch processes will be converted to continuous and streaming data processing. But to ensure the scale and latency requirements, data has to travel in the shortest path from creation to value. This means that elaborate complicated technology stacks will start to impede progress. Fewer layers touching the data and doing more when they touch will be the evolving pattern.

Q: How are current BSS failing to meet the new latency requirements of 5G? What changes need to be made?

A: Many of the BSS solutions out there are based on aging and tired technologies of yesteryears. With the demands that 5G is placing, Tier 1 and Tier 2 operators are already evidencing the inadequacies of these systems in meeting the speed, scale and latency requirements. The changes in core architecture to a service-based model is transitioning many of the network functions to become real-time even if they were batch oriented in the past. 

With the BSS vendors aligning with the micro services architecture, it is not the application level that is going to be expressing scaling problems; it is the data layer that will experience scale, and consequently, data consistency problems at scale. BSS solutions, in their journey to address 5G architectural changes and needs, must revisit the data layer choices from previous generations to modernize to ensure they can meet the scale and latency expectations of the present and future. A modern data platform unifies the ability to ingest, store and process data in order to drive decisions for network function altogether while being horizontally scalable, durable, highly available and replicated across geographies for resiliency.

Q: What about revenue assurance? How is that changing? 

A: Previous generation revenue assurance centered around detecting, and in some advanced cases preventing, usage fraud. With the rise of IoT use cases, CSPs will need to ensure that not only do the fraud scenarios encompass usage, but also include intrusion and malware fraud. With the increased number of charging triggers proposed in the Release 16 specs, these trigger points can in addition to providing information for charging, can also supply the necessary information for protective measures such as intrusion detection, bot attack prevention and unauthorized access prevention.

Q: What else is required, from Volt Active Data’s perspective, to adequately monetize 5G?

A: With the increasing data generation rates, just processing data in some data lake to analyze and learn will not suffice. The agility that is required to adapt the systems to the ever changing environment would require operationalizing the learnings. There are two types of moments in any system: Ones that give an opportunity to increase revenue through upsell, cross sell or even customer acquisition and ones that are indicating that something malevolent is shaping up to culminate in the compromise of the network or data or expose the network users to harm. Either of these types of moments need to be acted upon before the context has changed and the decisions and actions are not germane anymore. It is important to not just meet scale and latency for simplistic operations but it is, and will continue to be, important to learn from data the current conditions and be able to incorporate those learnings into the automated decision making process. Monetization and security cannot be reconciliation exercises but need to be incorporated and intertwined into the day-to-day processes in an automated manner.

For a more detailed look at how the telecoms sector is working to monetize 5G investments, register for free for the virtual 5G Monetization Forum on Feb. 15.

ABOUT AUTHOR

Catherine Sbeglia Nin
Catherine Sbeglia Nin
Catherine is the Managing Editor for RCR Wireless News and Enterprise IoT Insights, where she covers topics such as Wi-Fi, network infrastructure and edge computing. She also hosts Arden Media's podcast Well, technically... After studying English and Film & Media Studies at The University of Rochester, she moved to Madison, WI. Having already lived on both coasts, she thought she’d give the middle a try. So far, she likes it very much.