Object processing method and device based on big data, equipment and storage medium

Abstract

The embodiment of the invention belongs to the field of big data, and relates to a big data-based object processing method, which comprises the steps of establishing a data warehouse of evaluation objects, the data warehouse comprising evaluation databases of all the evaluation objects, and the evaluation database of each evaluation object comprising parameters of multiple dimensions; calculatinga comprehensive capability value of each evaluation object by adopting a predetermined function according to the parameters of multiple dimensions included in the evaluation database of each evaluation object; respectively comparing the comprehensive capability value of each evaluation object with a threshold value to eliminate the comprehensive capability value of the evaluation object smaller than the threshold value so as to obtain the comprehensive capability value of the evaluation object greater than or equal to the threshold value; sorting the comprehensive ability values of the evaluation objects greater than or equal to the threshold value according to a descending order, and sending the sorted comprehensive ability values of the evaluation objects to a display for displaying. Theinvention further provides an evaluation object processing device based on big data, computer equipment and a storage medium.

Description

technical field [0001] The present application relates to the technical field of big data, and in particular to a big data-based object processing method, device, computer equipment and storage medium. Background technique [0002] In work or life, it is often necessary to evaluate the ability of a specific object, for example, to evaluate employees in the workplace, for example, the supervisor’s subjective impression combined with the quality and quantity of work completed to evaluate whether an employee is qualified, good or excellent, and There is a possible way of evaluating, for example, recording the employee's performance through a notebook or computer during the work process, and then reviewing the record at the end of the year to evaluate the employee. However, in the workplace, whether it is human resources, supervisors or leaders, the evaluation of employees' work ability or growth prospects is generally based on the employee's usual performance or work result-ori...

AI Technical Summary

Problems solved by technology

However, in the workplace, whether it is human resources, supervisors or leaders, the evaluation of employees' work ability or growth prospects is generally based on the employees' usual performance or work results-oriented, but this evaluation will be based on the evaluation views of different reviewers or Preferences vary. Therefore, personnel, supervisors or leaders have no way to intuitively understand the real ability and work performance of shop assistants. They can only evaluate employees based on one-sided impressions. The career planning of shop assistants can only be carried out through the employees' own career planning, which is not intuitive. For example, the evaluation of employees mainly depends on the intuitive impression of the supervisor or whether the project is completed or not, without a comprehensive data evaluation, a scientific evaluation system or a unified evaluation method cannot be formed, and the evaluation results are subject to subjective The influence of factors is large, the evaluation effect is not good, and the efficiency of manual evaluation is low, and the accuracy is not high

[0003] Moreover, even if a computer is used to record through excel, all data needs to be recorded, but when the amount of data is very large, such as tens of thousands of data, when the computer records and processes through excel, it takes up a lot of memory resources and Central processing unit (Central Processing Unit, CPU) resources can easily lead to slow processing speed and even blue screen of death

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