It is a critical problem to uniformly allocate a large number of virtual machines at the cloud clients to the physical hosts at the cloud data centers. To this end, a greedy algorithm optimized virtual machine allocation approach for cloud data centers is proposed in this paper. First, a working scenario is designed for the enterprise-oriented cloud data centers, including three layers, a user layer, the layer of cloud service provider, and the star layer of cloud data centers. Specifically, the user layer is used to generate the request sets of the virtual machines, and the layer of cloud service provider allocates a large number of request sets of the virtual machines at the user layer to the bottom cloud data center through the classical bin packing algorithm. Then, the mathematical models considering different constraints are established during the allocation of the virtual machines. Finally, the virtual machine allocation among the cloud data centers is optimized using the greedy algorithm. In addition, the big data center of an enterprise is taken as the cloud testing environment, and the test results show that the classical Best-Fit-Algorithm (BFA) performs well in virtual machine allocation and consumes little energy of cloud platforms, providing a reference for the construction of cloud data centers in other enterprises.