Big Data Mining Method of Workplace Human Behavior Analysis for Enterprise Performance Acquisition

Abstract

At present, the behavior research of enterprise performance data has become the focus of current research, but there are still many problems in the reliability and accuracy of the data, and it involves extensive disputes such as privacy and predictability. Based on this, this paper studies the big data mining method of workplace human behavior analysis for enterprise performance acquisition, and constructs a behavior data observation system architecture integrating high-precision, all elements and multiple perspectives. This paper discusses the scale dependent characteristics of behavior change, the differentiation and integration of individual behavior and group behavior data, the definition of behavior data demand and individual privacy boundary, and the analysis, matching and integration of behavior data. This paper attempts to define the comprehensive collection and integrated processing of behavior data from the following aspects: boundary definition and data demand of scientific problems, multi-source data collection and integration method, multi factor behavior data analysis and integration method, and application driven behavior data application mode and approach. Finally, the experiments show that the big data mining method of workplace human behavior analysis for enterprise performance acquisition has high accuracy and effectiveness in the practical application process, which fully meets the research requirements.