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Data quality control method and system based on block-level data collection

A data quality control and data collection technology, which is applied in the direction of electronic digital data processing, digital data information retrieval, special data processing applications, etc., can solve the problems of restricting the development of enterprises, out of control of data progress, and uneven quality, so as to ensure comprehensive performance and timeliness, enhanced management and control capabilities, and accelerated construction progress

Pending Publication Date: 2021-11-05
中建材信息技术股份有限公司 +1
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AI Technical Summary

Problems solved by technology

However, large-scale enterprises involve a wide range of businesses, resulting in complicated data resources, which are prone to out-of-control data progress, uneven quality, and data confusion, making it difficult to collect and dispatch data well, thus affecting the construction quality of enterprise information systems, and even Bring more uncontrollable data risks to enterprises, thus restricting the development of enterprises
However, there is currently no relatively complete method and system for controlling the quality of enterprise data

Method used

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  • Data quality control method and system based on block-level data collection
  • Data quality control method and system based on block-level data collection
  • Data quality control method and system based on block-level data collection

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Embodiment 1

[0072] Such as Figure 1-Figure 4 As shown, the purpose of this embodiment is to provide a data quality control method based on block-level data collection, including the following steps:

[0073] S1. Based on the blockchain and shared distribution network, build a data model, build a distributed database on each block node, and connect to internal and external business systems, collect and process data from the server at the proximal end of each node;

[0074] S2. Define data-based business requirements at each block node, convert business requirements into data requirements, and compile corresponding data flow diagrams;

[0075] S3. Based on the data flow diagram, evaluate the data quality and the corresponding business impact of the data in the data flow, and locate the problems existing in the data quality through in-depth analysis;

[0076] S4. According to the quality problem, formulate a data quality rectification plan, implement the plan, control the quality of the da...

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Abstract

The invention relates to the technical field of data quality management, in particular to a data quality control method and system based on block-level data collection. Comprising the steps of building a data model based on a block chain, converting a business demand into a data demand, positioning a data quality problem, implementing a rectification scheme to control data quality, generating an evaluation report and the like. According to the method designed by the invention, the enterprise data collection platform is established on the basis of the block chain, the comprehensiveness and timeliness of the data can be ensured, the data value can be better presented by controlling the quality of the data and ensuring high-quality data, and thus more commercial values can be obtained through the high-quality data; a corresponding system manages business data through a distributed database, can quickly discover data quality problems, rectifies the data according to standard data, further predicts and avoids quality risks possibly existing in future data, can realize online supervision of enterprise business data, and improves data quality.

Description

technical field [0001] The present invention relates to the technical field of data quality management, in particular to a data quality control method and system based on block-level data collection. Background technique [0002] For enterprises, the most important asset is data, that is, the core value of data can be understood as core business value. Realizing the value of data requires business data analysis and value mining. At present, there are no problems with conventional data analysis methods and technologies. As long as there is clean and complete data, the value of data can be well presented, but ensuring data quality is the key to big data. A prerequisite for bringing value to the business. Most traditional enterprises have no awareness of quality management of data resources, and do not know how to implement data governance, resulting in poor data quality, such as missing data, data islands, data distortion, etc., resulting in the inability to use data resource...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/34G06F16/215G06F9/50
CPCG06F11/3409G06F9/5072G06F16/215G06F2209/502
Inventor 易世勇史子超邢宏浩
Owner 中建材信息技术股份有限公司
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