Enterprise management data analyzing and processing system and method

Abstract

The invention relates to the technical field of enterprise management, in particular to an enterprise management data analyzing and processing system, and further relates to an enterprise management data analyzing and processing method. The task scheduling system comprises a to-be-scheduled task generation module, a to-be-scheduled task storage module, a task scheduling module and a task processing module, In the present invention, there is provided a camera device, The Hadoop system is used for data analysis at the bottom layer of the enterprise management data analysis processing system; onthe upper layer of the enterprise management data analyzing and processing system, the task scheduling module is used for realizing the overall management of the task; Compared with the prior art, themethod has the advantages that the Hadoop system can be utilized to perform data analysis, complex operations such as table dividing, table splitting and merging on the relational database are avoided, the data analysis process is simplified, and a system for scheduling and managing tasks more conveniently is provided.

Description

technical field [0001] The present invention relates to the technical field of enterprise management, in particular to an enterprise management data analysis and processing system, and in particular to an enterprise management data analysis and processing method. Background technique [0002] In recent years, due to the continuous growth of data in the Internet field, companies are faced with the need to process massive amounts of data. The data analysis within the department is mainly for the operation and maintenance services of various departments of the company. The data analysis is mainly based on the logs generated by the servers (Server) of each department, such as apache logs, nginx logs, etc. The purpose is to analyze user access and data based on these logs. The traffic has clear quantitative data in the time dimension, product line dimension, domain name dimension, etc., so as to provide suggestions for the company's server operation and maintenance management, tr...

AI Technical Summary

Problems solved by technology

[0007] However, as the scale of the website and the number of users continue to grow, the amount of data increases sharply. In the data analysis process of the existing technology, specific analysis results are obtained through complex table splitting, table splitting, and merging. The technical implementation process is complicated and requires specialized of maintenance personnel to maintain

Moreover, if new business analysis requirements need to be added, new analysis scripts need to be added, which is not conducive to expansion

[0008] To sum up, the data analysis methods in the prior art require complex operations such as table splitting, table splitting, and merging on relational databases, so the implementation process is complicated and difficult to maintain; moreover, the data analysis methods in the prior art are not Conducive to expanding new business analysis requirements

Images