On-demand computing-based data analysis device and method for analysis factors

Abstract

The invention provides an on-demand computing-based data analysis device and method for analysis factors. The on-demand computing-based data analysis device for the analysis factors comprises a configuration module, a data extraction module, an analysis factor computing module, a data analysis processing module and an analysis result output module. The on-demand computing-based data analysis device and method for the analysis factors, which are disclosed by the invention, have the advantages that the analysis factors and analysis rules are easy to expand, the timeliness and the accuracy can be guaranteed, the analysis factors can be computed on demand, and thereby the work efficiency and the performance of a system are markedly improved.

Description

Technical field [0001] The present invention relates to a data analysis device and method, and more specifically, to a data analysis device and method based on analysis factors calculated on demand. Background technique [0002] At present, with the increasing demand for information and data processing and the increasing variety of business types in different fields, data analysis based on analysis factors (that is, various analysis elements used in data analysis) has become more and more important. [0003] Generally, the basic principles of existing data analysis methods and devices based on analysis factors are as follows: extract original data from data sources; construct based on the original data and according to preset rules (the rules are predetermined based on each specific application) Data model and calculate each analysis factor at the same time; based on the analysis factor and according to preset rules (the rules are determined in advance based on each application req...

AI Technical Summary

Problems solved by technology

[0004] However, as business types become more and more abundant, more and more analysis factors need to be used in data analysis, and data analysis rules based on specific application requirements change more and more frequently, so it is necessary to frequently analyze factors and data Analysis rules are dynamically adjusted

Therefore, the above-mentioned existing technical solutions have the following problems: when the analysis factor needs to be expanded (that is, when the data analysis rule needs to use a newly added analysis factor), if the analysis factor is not within the range of the preset analysis factor, it cannot be analyzed according to the If the pre-set analysis factors are obtained through simple calculations, the system code must be manually modified, which cannot meet the real-time requirements of the system; at the same time, this method consumes more time, thus increasing maintenance costs, and because the process is cumbersome and easy to Errors reduce the work efficiency and performance of the entire system; in addition, when the data analysis rules need to be changed, the system code must also be manually modified;

Therefore, the above-mentioned existing technical solutions still have the following problems: the process of calculating all the analysis factors will consume a large amount of calculation time and system resources (that is, the calculation of a part of the analysis factors is useless), thereby significantly reducing the overall performance of the system

Images