Operators are facing disruptive change to their networks driven by technological and business forces. The business seeks to increase innovation, reduce costs, and manage risk while network technologies including virtualization, software defined networking, streaming telemetry, and automation drive additional complexity into the network. Typically, an operator's functional disciplines such as engineering, operations, analytics, and planning each have separate, uncoordinated views of the network with sometimes overlapping, sometimes disjoint, data, leading to inefficiencies and uncertainty. Network Digital Twin provides a comprehensive view of the network, combining disparate data sources such as telemetry, monitoring, inventory, provisioning, analytics, planning, and network automation with variable-fidelity models of equipment, network functions, network services, network operations, and analytics, creating a separate digital representation of the live network. The network digital twin is an integrated, consistent, comprehensive, lively, and accurate model of the network and its constituents, connected to and representing the state and behaviors of the actual entities of the operating network. Operators use the network digital twin through the accompanying dynamic views and visualizations to better understand the state and behaviors of the network and, through manipulation of the digital twin, affect changes in the actual network. Functional disciplines within the operator's organization use the network digital twin to break down data silos and leverage the consistent model of the network as the basis for their individual missions. The paper addresses the formation, concepts, and implications of digital twins and their application to the operator's network, including an example from Cox's application of aspects of digital twin to our data center network.