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NWDAF

Network Data Analytics Function: 3GPP 5GC NF (TS 23.288) collecting network data and providing analytics to other NFs for intelligent decision-making.

NWDAF is the 5G core's built-in analytics brain, standardised by 3GPP in TS 23.288. The idea is to stop every network function from reinventing its own data collection and instead give the core a common function that gathers data — from other NFs, from the OAM system, even from application functions — and hands back analytics that others can act on.

What it actually produces are things like load predictions for a slice, anomaly flags, abnormal-UE behaviour detection, and QoS sustainability forecasts. A consumer NF can subscribe to these and adjust: a slice could be scaled before it congests, or a policy tweaked when a device starts misbehaving. In newer releases NWDAF is split into logical pieces — an Analytics Logical Function and a Model Training Logical Function — which is what makes it a practical home for ML in the core rather than just a glorified counter aggregator. It's a foundational building block for closed-loop automation inside 5G.

Learn NWDAF in depthCovered in our Telecom AI/ML & Network Automation course — Apply AI/ML and zero-touch automation to telecom networks.

Want to truly understand NWDAF? Learn it in context.

NWDAF is taught inside our Telecom AI/ML & Network Automation course with diagrams and worked examples. The first module is free with an account; labs, TelcoMentor and the rest of the curriculum are on Pro.

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