Data quality analysis evaluation model facing electric power big data

Abstract

The invention discloses a data quality analysis evaluation model facing electric power big data. Core functions of the data quality analysis evaluation model facing electric power big data comprise steps of performing processing on a collection plan and a restriction rule in a basic model, calling a background storage realizing checking and analysis through a data quality control model, executingchecking and forming a checking result in an entity database, performing analysis, computing, classification and summarization through an analysis program, generating a quantized index result reflecting a plan completion state and data quality, storing the result in an analysis result table, and calling the analysis table through a foreground to generate a data quality analysis evaluation report which reflects various quantized indexes of data quality problems in detail. The invention improves an automated level of data quality analysis and evaluation, realizes intelligent management and control of data quality, satisfies data quality control requirement for big batch data, and realize quantized analysis and evaluation for data integrity, timeliness, accuracy and consistency.

Description

technical field [0001] The invention relates to the technical field of intelligent power distribution and utilization, in particular to a data quality analysis and evaluation model for electric power big data. Background technique [0002] With the rapid development of the power system and the continuous deepening of the informatization process, the number and types of business data in the information system are gradually increasing, and the demand for data sharing is urgent. As a resource, data has the characteristics of multi-disciplinary, high data collection density, high frequency, and complex data processing process. It is the main body supporting the construction and application of informatization. At present, the power part has accumulated a large amount of power statistical data, among which there will inevitably be abnormal, redundant or incomplete data. Data mining algorithms require that there are huge challenges in accurately mining effective information. There...

AI Technical Summary

Problems solved by technology

At present, the power part has accumulated a large amount of power statistical data, among which there will inevitably be abnormal, redundant or incomplete data. Data mining algorithms require that there are huge challenges in accurately mining effective information. There are many meaningless components in massive actual data, which seriously affects the execution efficiency of data mining algorithms. With the deepening of applications, repeated data entry and storage, and data quality The improvement of data quality has be

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