Making Intelligent Automation a Reality with Advanced Analytics At Ciena, we call this the Adaptive Network. But now, vendors are augmenting traditional analytics with automation and artificial intelligence technologies to enable the next generation of highly intelligent networks-a network capable of dynamically self-configuring or self-optimizing based on changing network conditions. Typically, this type of operation has been a manual process. For example, if a network operator finds that there may be a congestion problem in a certain area of the of the network, traffic can be routed through a different part of the network to meet service performance objectives. Once identified, operators take the next step of ‘acting’ on this data-which typically involves a network operation or a set of operations. Network analytics, in its simplest definition, involves the analysis of network data and statistics to identify trends and patterns. As a result, they are able to make smarter, data-driven decisions about their operations that help them achieve their desired business outcomes. Now, in pursuit of serving customers more effectively and looking for every possible competitive edge, network operators are utilizing analytics to gain a deeper understanding of the network. Networks are at the center of today’s world, so understanding how the network is performing is critical-not just for technical peace of mind, but for the operation of the business itself. Services and support Services and supportįeatured Article Taking a software-driven approach to sustainability.
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