AVA - Network Data Analytics Function
5G network analytics help CSPs to create new revenues
Data analytics helps CSPs to improve customer experiences and use their 5G investments to create new sources of revenue. It also enables more predictive and proactive network operations.
What is NWDAF in 5G?
The Nokia AVA NWDAF is a new network function that collects data from 5G Core network functions, performs network analytics and provides insights with closed loop automation to authorized data consumers. These include external users taking advantage of open APIs to help generate greater innovation and unlock new value. Nokia’s distributed NWDAF architecture makes analytics available where needed to meet the varying latency requirements of 5G use cases.
Nokia AVA NWDAF complies with 3GPP specifications for the 5G Standalone Core and offers unique and valuable propositions beyond the standards. This standard approach to collect, analyze and expose data allows CSPs to manage, automate and optimize their 5G network operations much more efficiently.
Nokia AVA NWDAF is cloud-native, multi-vendor capable and probeless solution, making it easy to collect and analyze data from networks and services. It is part of the Nokia AVA analytics and AI product range, offering software-as-a-service (SaaS) delivery and consumption models to quickly deploy new applications in an agile manner.
About our AVA Network Data Analytics Function demo
The NWDAF demo shows the opportunities and benefits our telco analytics tool brings to CSPs, enterprises and ecosystem players. You will also learn about the edge/central architecture and its benefits and how our network data analytics tool can help you to provide analytics at the network edge and to enable ML/AI driven network automation. Our NWDAF demo also showcases key network analytics use case examples: e.g., teleoperation of autonomous vehicles, drones and network traffic rerouting based on NWDAF predictions with real-life material from our partners.
Discover our AVA NWDAF demo
Why does 5G analytics need distributed architecture?
The Nokia architecture includes an edge NWDAF co-located with Core Network Functions (NFs) and a central NWDAF. The edge NWDAF serves low/ultra-low latency use cases while the central NWDAF supports use cases that do not have real-time requirements and includes functions such as the data and Machine Learning (ML) models repository for the continuous training of AI/ML models.
How is network analytics beneficial to businesses?
5G use cases with predictive network analytics and insights help to monetize 5G network insights and increase innovation and new business with Nokia AVA NWDAF.
Why is predictive QoE important for many 5G use cases?
In the enterprise domain, promising enterprise use cases range from autonomous vehicles and robots to 5G drones, while cloud gaming will create consumer demand for low and consistent latency to deliver an enjoyable user experience.
Network performance and reliability are critical considerations in 5G use cases, from autonomous vehicles and their remote operation, to public safety cases. NWDAF plays a key role here. It can help CSPs make 5G proactive and predictive for their partners for such 5G use cases. Predictive analytics makes QoE itself more predictable, needed by use cases such as autonomous vehicles, delivery robots and 5G drones.
Why is an ecosystem of partners important?
Nokia AVA NWDAF enables a wide range of use cases jointly created with customers and partners. Using open APIs, CSPs can share network insights with an ecosystem of partners and jointly create valuable propositions. CSPs could also use an open ecosystem to create a 5G ML marketplace of applications.
Nokia AVA NWDAF and Google Cloud - unlocking the value of network data
Data is a strategic asset for Communications Service Providers (CSPs) striving to meet business priorities and achieve digital transformation. Analyzing and offering business insights based on network data improves customer experiences and helps CSPs use their 5G investments to create new sources of revenue.
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