Network Data Layer, a new way to look at data in Telecommunication networks

Article originally published in Forbes Technology Council @

Network Data Layer, a new way to look at data in telecommunication networks

Every telecom system is bursting with information about subscribers, services, and devices – not to mention the telco’s network equipment and operational status. This data is both sensitive and necessary for the core business, and in mobile communications (compared to fixed), there is even greater sensitivity as location and current session information is needed to establish and maintain connectivity. Recent data breaches [1] and network outages in telecom operator networks have made headlines and eroded trust, given the large-scale effects on customers and on the business operations of the telecom operator themselves.   This means that how data is stored, distributed, and shared among multiple applications in the networks, demands the highest attention of business owners.

Against this backdrop, where data is critical asset and rules of access and storage security urgently need harmonizing, there is another business imperative – to manage overall costs. Telecom operators are under pressure to continue to deliver a dividend to shareholders. This is while undertaking extensive modernization programs that are needed to simultaneously reset their cost base and processes, at the same time as equipping them with architectural platforms that support service innovation and drive efficiency and quality through automation.

For most operators this means moving to hybrid cloud environments, migrating legacy systems, and creating a strategic architecture to develop new services on 5G and for internet of things (IoT) that can scale. So, can a telecom operator do both? The software infrastructure depends on data just as much as it does on new containerized or cloud-native environments. After all, the data that is provisioned for new devices must be stored somewhere, as does the data that is generated as users move around.

The challenges of data

This all seems quite logical, so one might wonder why telcos find themselves in such an expensive dilemma. Simply put, as networks have evolved, each of the applications and systems have brought their own data storage with them,So, an operator may find today, that they have data spread across a dozen different systems, perhaps duplicated, not synchronized, and certainly not under their full control to plan and manage.

Looking at data as a common, key asset was first formulated by the industry initiative NGMN (Next Generation Mobile Networks), who put forward the paper on a “Network Data Layer Concept[2]. The tenets of this paper are that operational change is not just about the platform the software is running on but also about the data it needs to perform its task and the outputs it generates as it completes its function. Without considering a common approach to data, the result will be a patchwork of technical approaches leading to variable access times, cost of operation, and potential inhibition to move to large-scale new IT environments.

Moving from concept to reality is harder. In most telecom infrastructure, you are dealing with incumbent players whose inertia is not just about change but who are also concerned about losing control of the data. As data is inherent to a specific function or application, the ownership of that data becomes a leverage point that vendors of the various functions are not motivated to give up. This is why the Network Data Layer concept has always had ownership of the data model at its heart. The model deliberately puts “the right to change and customize” into the hands of the owner of the data, ie the mobile communication service provider.

Where are we now – and the path forward?

The imperative to manage costs, modernize and set a strategic direction for a more distributed network is increasing. Telecom operators are forging new relationships with cloud vendors (see: AT&T and Microsoft[3], Deutsche Telekom / Google[4], and Verizon/AWS [5]). Telcos need to simplify and control their data models to develop and deploy AI and automation. Additional examples of utilizing data in new ways we can see in the market:

  • Deutsche Telekom/Google: innovating new service & user experience[6]
  • Telstra/Quantium AI partnership: B2B applications, customer analytics, fraud detection and operations[7]
  • Singtel: Autonomous network developments[8]

The adoption of 5G standards and interworking has matured (in the 5G environment, data is treated as resources and addressed by URLs) and acted as an enabler for change. Implementing 5G Core standard is an ideal point of change, yet a joint view of data structures for different network functions is missing. A simpler, strategic, way to handle data in telecom networks, based on a Network Data Layer concept, will save both time and costs for service providers struggling to improve their profit margins in a competitive industry with increasing operational costs. Additionally, new revenue streams, based on the monetization of subscriber and network data, are possible, provided limitations around data access are overcome. It’s time to get the fundamentals right, and a Common Network Data Layer is key to achieving this.

Article originally published in Forbes Technology Council @

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