Production Security Evaluation Strategy of Power Data Center Based on Data Warehouse

This paper studies the task scheduling strategy of cloud data center based on data warehouse. Combined with the characteristics of power data center, a multi-qos evaluation model for power data center is defined. In this paper, a neural network algorithm is used for task scheduling with QoS overall effect value as the target. Then this paper establishes the overall technical architecture and hardware and software system of the big data center of the electric power company, and studies the key technologies such as data access and preprocessing, data integration and storage, data computing and processing, data mining and analysis, data security and management. Finally, taking the transformer equipment status evaluation experiment center as an example, the tasks of fault diagnosis, status evaluation, overhaul and maintenance are simulated and scheduled, and the Cloud Sim platform is used for simulation test. The results show that this algorithm can meet the multi-qos requirements of power users to the maximum extent and effectively improve the efficiency of power data center operation.