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Collaboration Is Key Ingredient in Predictive Analytics & Network Automation

James Crawshaw
5/8/2018
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Data analytics solutions involve collecting and cleaning data; identifying and interpreting patterns; and generating actionable insights that deliver business value, typically cost reduction or revenue growth.

These solutions have many, many uses. They could be applied in the Network Operations Center (predictive faults, proactive resolution, congestion relief), network planning (capacity tracking), marketing (personalized services), or customer care (SLA monitoring, troubleshooting), to name a few use cases.


To compete with the OTT players, telcos need to be nimbler by accelerating network automation. Join us in Austin, Texas from May 14-16 for our fifth-annual Big Communications Event as we tackle challenges like automation. The event is free for communications service providers -- secure your seat today!


Network operators can easily fill huge data lakes with streaming telemetry about network paths, traffic flows and performance. The hard part is unlocking the value of all this data to deliver value such as faster cause analysis, reduced mean time to repair, or detection of security threats. To achieve this might require advanced machine learning algorithms that can do predictive or prescriptive analytics.

It might also suffice to use traditional statistical analysis and correlations. There is no one-size-fits-all approach to analytics.

Successful implementation of analytics to solve a business problem in telecom depends on combining expertise from multiple fields, including data science, computer science and network operations. The ideal solution will involve a DevOps approach that fosters effective collaboration across different parts of the telco organization.

Ideally, we should be able to take the output of our analytics process and feed this directly into operational processes in an automated closed loop. This requires that the analytics solution is integrated with existing policy systems (to ensure network integrity is maintained) and orchestration systems that (subject to policy approval) implement the recommendations of the analytics platform. Using predictive analytics to drive network automation is a key priority for telecom operators with significant scope to add business value.

To find out more, join us in Austin May 14-16 to boost your knowledge about how data analytics can support the journey toward virtualization and automation in the network, for the fifth-annual Big Communications Event May 14–16. The event is free for communications service providers – secure your seat today!

— James Crawshaw, Senior Analyst, Heavy Reading

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