RETRACTED ARTICLE: Application of hardware system of temporal big data in enterprise human resource management in distributed environment

Abstract

Distributed data collection systems are often used in many fields, such as industrial control, power systems, seismic monitoring, and ocean exploration. In a distributed data collection system, the time of data collection and the efficiency of data collection are all related to the accuracy of the data. Subsequent analysis and processing show that the distributed data collection system is a very important performance indicator: this article combines the timing factors of the timing rules in the dataset, and after normalization and expansion, the rules will be edited according to the effective voting rate. Perform a weighted sum calculation on the rules in the edited sub-database to obtain the final timing rules. Finally, the algorithm is implemented by pseudo code. With the rapid development of information technology, we have entered the era of big data. Big data has the characteristics of resource sharing, large storage capacity, and high speed, so it has been widely used in various fields. In the context of the rapid development of the modern economy, the human resources department has provided a relatively complete infrastructure system for many large companies. It can be seen that the work of the personnel department is gradually becoming an important factor in the development of the company. Appropriate implementation of big data in the company’s human resource model can integrate resources into the industry and the company, improving operational efficiency, and laying a solid foundation for the company’s sustainable and long-term development. This article first outlines the hardware system and company management of temporal big data in a distributed environment, discusses in detail the needs of human resource management in companies in the era of big data, and proposes a suitable human resource management model.