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Guavus Blog

All the latest from the world of Guavus

NWDAF: Automating the 5G Network with Machine Learning & Data Analytics

NWDAF: Automating the 5G Network with Machine Learning & Data Analytics

There’s a common pain point among communications service providers – how to integrate analytics into the network, currently the analytics are complex from the many non-standardized interfaces and inconsistent data collection techniques across network vendors. These concerns may finally be addressed by the network data analytics function (NWDAF).

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Guavus-IQ_What_is_under_the_hood

Guavus-IQ: What’s under the hood?

For CSPs, understanding how their network is utilized by their subscribers and how the subscribers experience the network and services are the significant factors influencing their revenue and business value. Guavus, today announced Guavus-IQ, a comprehensive product portfolio that provides a multi-perspective analytics experience for CSPs.

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Mobile customers looking at videos

Four Ways CSPs Can Use AI to Gain New Subscriber Insights, Out-Market OTT Competitors and Deliver a Better Customer Experience

Most CSPs know they need to harness their valuable data, but struggle with how to do it. Putting AI and analytics tools to work alongside their deep-packet inspection (DPI) classification engines, providers can learn a lot more about their customers, then categorize them in understandable ways that allow the provider’s marketing department to approach them with targeted, personalized and meaningful service offers. Let’s examine a few ways CSPs can succeed.

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5G in use

5G: Too Good to be True?

5G promises both tremendous opportunity and challenges. Leveraging AI and analytics, CSPs can take the volume of data generated by the network and turn it into useful, consumable information that helps them grow their business and increase their top line.

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Root issue analysis is the key to network alarm management

Get to the Root of It.

Guavus analytics experts explain how applying root issue analysis will drastically reduce the number of network alarms, reveal the hidden structure of issues and clearly identify the strength of the relationships between the issues.

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