Preprocessing Method of Structured Big Data in Human Resource Archives Database

In order to solve the problem of false report and concealed report, this paper studies the characteristics of human resource and wage information statistics data, proposes the preprocessing method of structured big data of human resource archives database, adopts the outlier detection technology of data mining, and designs an adaptive detection method of human resource file data based on Hybrid clustering. In depth analysis of the advantages and limitations of big data preprocessing method, combined with the advantages of the two algorithms, make up for the limitations of the human resource file database structure, so that the detection process can eliminate manual intervention, and achieve the ability of adaptive calculation of initial parameters. Through the preprocessing method of structured big data of human resource archives database, the abnormal data in human resource statistical data is found. In order to verify the pre-processing method of structured big data of human resource archives database proposed in this paper, the enterprise data of enterprise wage summary table collected by statistics bureau is used. The experimental results show that the method can achieve the effect of expert detection in the detection of abnormal data, which can provide reference for the statistical department.