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Networks that learn and improve

Learn how to build data-driven networks with Ericsson’s NWDAF

5G network data analytics function (NWDAF)

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5G network data analytics function (NWDAF) is designed to streamline the way core network data is produced and consumed, as well as to generate insights and take actions to enhance end-user experience. Learn how Ericsson’s unique value proposition allows you to benefit from the standard.​

What is 5G network data analytics function?

Watch this video to understand the value of Ericsson's NWDAF | 2 min.

NWDAF is designed to overcome market fragmentation and proprietary solutions in the area of network analytics, streamlining the way core network data is produced and consumed, as well as generating insights and taking actions based on these insights.

NWDAF addresses three primary standardization points:

  • Data collection interface from network nodes
  • Predefined analytics insights
  • Data exposure interface for consumers

Ericsson has been active in 3GPP since its inception and has helped shape NWDAF as standard, ensuring it promotes a multi-vendor approach to avoid vendor lock-in.

With Ericsson’s NWDAF solution, service providers will be able to evolve to the standard smoothly, benefit from decreased TCO while using the standard and use analytics models on top of the standard.

Benefits with 5G network data analytics function

01

Smooth journey to 3GPP standard through well-established Ericsson cloud native products.

02

Up to 45% lower TCO through smart data acquisition, efficient integration, optimized lifecycle management and orchestration.

“At BT we connect for good and our customers increasing reliance on the network requires us to think differently - with Ericsson we are working on cloud native solutions for 5G Core architecture to support multiple generations of technologies, and we see the need for greater automation and analytics to manage complex networks and ensure the best quality experience for our customers. I’m pleased to see that Ericsson is launching NWDAF building upon Ericsson’s built-in software probes and Expert Analytics (EEA), a natural next step development to enhance closed loop automation and service assurance that could benefit BT’s Customer Network Experience (CNE) platform.” - Neil McRae, Former MD Architecture & Strategy, BT Group Chief Architect

Learn more about Ericsson’s NWDAF​

In focus

How is Ericsson’s NWDAF making networks even smarter? | Video | 10 min.

Glen Gilmore and Ericsson's Monica Zethzon discuss our NWDAF launch, and how our new network function makes networks smarter and more flexible.

Capitalizing on cloud native in NWDAF use cases | Blog post | 8 min.

NWDAF is enhancing network operability by enabling smarter networks that learn and improve. We take you on a deep dive into how NWDAF is enabling advanced use cases.

NWDAF: the blessing 5G Core needs to reach a data-driven network | Blog post | 9 min.

Take a closer look at NWDAF and explore what lies ahead for data-driven networks.

Ericsson enables smarter networks that learn and improve | Press release | 2 min.

We are launching Network Data Analytics Function (NWDAF) solution, based on smarter data-driven networks that learn and improve.

"Ericsson’s NWDAF adds intelligence to the 5G core, bringing new insights that enable automation and optimization. With this solution, Ericsson shows its technology leadership in 5G Core." - James Crawshaw, Principal Analyst, Telco IT & Operations, Omdia

NWDAF in monetization

NWDAF enables CSPs in generating new revenue streams building on the network data and insights. Some of the NWDAF use cases such as predicted mobility, slice service-level agreement (SLA) assurance help in generating new revenues. ​

Ericsson’s NWDAF paves the foundation for CSPs to take use-case driven approach where insights based on data, could be used to close the loop by taking actions as well.

NWDAF could expose network insights to external application function via network Exposure Function (NEF) to create new use-cases.

To learn more about the use-case driven approach, and recommendation to accelerate the speed of AI adoption in CSP networks, read our white paper.​

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