Risk data filtering and storing method

Abstract

The invention discloses a risk data filtering and storing method which comprises the following steps: acquiring risk data to be stored, and extracting data basic information in the risk data to be stored; performing primary authentication on the basic data information according to a preset rule, and determining the legality of to-be-stored risk data; when the to-be-stored risk data is authenticated to be illegal data for the first time, conducting conventional configuration processing on the basic data information, conducting re-authentication on the basic data information obtained after conventional configuration processing and when the to-be-stored risk data is still illegal data through re-authentication, returning the risk data to be stored and when the to-be-stored risk data is authenticated to be legal data for the first time or the to-be-stored risk data is authenticated to be legal data again, performing verification processing on the to-be-stored risk data, filtering invalid risk data to obtain filtered risk data, and storing the filtered risk data in a risk library.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method for filtering and storing risk data. Background technique [0002] With the continuous development of the Internet and big data technology, the collection, statistics, and analysis of massive user data have become more and more important. In the field of electric power, it is usually necessary to collect risk data information related to project engineering in order to continue subsequent statistical and analysis work. In traditional data collection work, the staff directly transmits and stores risk data related to project engineering in the risk database to complete Data collection work. [0003] Due to the high accuracy of data required for the analysis of risk data in the power industry, the risk data stored in the traditional data collection method will be affected by the redundancy of massive big data, resulting in the storage of some non-risk data in the ri...

AI Technical Summary

Problems solved by technology

[0003] Due to the high accuracy of data required for the analysis of risk data in the power industry, the risk data stored in the traditional data collection method will be affected by the redundancy of massive big data, resulting in the storage of some non-risk data in the risk database. , this part of the impurity data will have a certain impact on the analysis work in the subsequent analysis process

Images