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Predictive analytics: Your key to preventing network failures

John Edwards | July 18, 2017
Powerful new tools replace crystal ball predictions with deep and actionable insights.

CIOs also need to set a predictive analytics strategy and roadmap that ties to business needs. "Within the scope of this strategy, pick a manageable goal that could be used as a proof-of-concept," Mir says. "The next step is to figure out all factors that contribute to its variability and get access to any and all data/logs available for the variables."

"The best way to get started with predictive analytics is not to start with predictive analytics, but rather to start understanding and identifying patterns of behavior across systems," Crupi says. "These patterns set the foundation for applying predictive analytics."

Once a predictive analytics platform has been deployed, feed the machine learning models with a significant amount of training data, Kastanis advises. Then rely on human experts to validate the initial predictions and execute changes in networks with expert approval until the accuracy of the ML models rise consistently above baseline expectations. "Until there are solid case studies to prove the accuracy of ML models, operators will be skeptical in taking the risk to let ML models make network changes for autonomous network management," Kastanis says.


A worthwhile effort

Predictive analytics is not a solution, it's a tool derived from strategy, Crupi says. "It is just one part of an overall analytics arsenal," he notes.

"Many organizations want to jump into predictive analytics and immediately start training models to predict failure," Crupi says. But that's really not a good idea. "Training a predictive model takes a tremendous amount of data and requires data scientists with access to historical context," he explains. "It’s best to start with basic analytics and visualizations so you can start to 'see' what is happening."

Reflecting on his own experience, Kastanis says that the benefits predictive analytics provides are worth all of the time and effort needed to structure and deploy the technology. "It is an amazing idea that will significantly stabilize network performance and optimize OpEx for network management, thereby making network management much more effective," he says.


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