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Data quality detection method based on spatial dispersion principle

A technology of data quality and detection method, which is applied in the field of data quality detection based on the principle of spatial dispersion, can solve the problems of relying on the subjective selection of the scorer and cannot achieve intuitive effects, and achieve the effect of simple and clear display results and intuitive and effective effects.

Inactive Publication Date: 2017-02-15
国网甘肃省电力公司信息通信公司 +2
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Problems solved by technology

[0003] Most of the existing data quality detection methods are based on database or software to achieve data quality marking, relying too much on the subjective choice of the rater at the time, most of the results are expressed in tables or text, which cannot achieve simple and clear intuitive effects

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  • Data quality detection method based on spatial dispersion principle
  • Data quality detection method based on spatial dispersion principle
  • Data quality detection method based on spatial dispersion principle

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with accompanying drawing:

[0023] A data quality detection method based on the principle of spatial dispersion, comprising the following steps:

[0024] S1: Build a data quality inspection model:

[0025] M=

[0026] Among them, M represents the data quality, D represents the data node that needs to be detected, I represents the data index corresponding to the data node, R represents the set corresponding to the data index, W represents the weight assigned to the rule R, and E represents the rule R Given the expected value, S represents the final result given to the rule R;

[0027] In this step, the value range of the weight value given to the set R is an integer greater than 0, which describes the proportion of the set in all sets; the expected value E given to the set R is the expected value of the rule before detection The obtained result is a real number between 0 and 100, and the final resul...

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Abstract

The invention relates to a data quality detection method based on a spatial dispersion principle. The data quality detection method comprises the steps of: (1) constructing a data quality detection model; (2) calculating a data quality absolute quantization value; (3) calculating a data quality relative quantization value; (4) and displaying a data quality detection result according to the data quality relative quantization value. According to the data quality detection method based on the spatial dispersion principle, the data quality detection result is demonstrated in the form of a graphic interface through calculating the data quality relative quantization value, the demonstration result is simple and clear, the effect is intuitive and effective, and the purpose of data quality quantitative display can be achieved quickly.

Description

technical field [0001] The invention relates to the technical field of data quality detection, in particular to a data quality detection method based on the principle of spatial dispersion. Background technique [0002] With the rapid development of information technology, data has gradually become one of the most important resources to realize the business value of enterprises. However, as the amount of data continues to increase, data quality issues also follow. Missing data, errors, inconsistencies and other problems hinder the application of enterprises, and even cause enterprises to make wrong decisions, lose important value and cause a crisis of trust. For these dirty data, many data quality detection and cleaning schemes have emerged as the times require. Data dependence is a data quality problem that is more difficult to detect. Since the system often does not know the logical relationship between fields hidden in the data table, data dependency issues are general...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F9/44
CPCG06Q10/06395G06F8/38
Inventor 段军红马志程杨鹏杨波胡珊珊曹玮润蔡玺魏军杨栋枢王维佳胡志亮高少鹏王超刘云
Owner 国网甘肃省电力公司信息通信公司
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