Data governance system and method

Abstract

The invention discloses a data governance system and method. The system comprises a data access module which is used for reading multi-source heterogeneous data, enabling the multi-source heterogeneous data after data exploration and data definition to be accessed to a big data center, and carrying out the data account checking; the data processing module is used for extracting data, converting the extracted data into a required format, correcting or clearing abnormal data, and distributing the data to a corresponding data warehouse; the data organization module is used for storing the distributed data into a corresponding library in a classified manner to obtain various types of metadata; the data processing module is used for carrying out directory integration and grading classification on the metadata, determining the blood relationship and quality of the metadata, carrying out data operation and maintenance and carrying out use and service on the metadata; and the data service unit is used for providing data for users. The invention solves the technical problems that unified data quality evaluation standards and management specifications do not exist in data quality monitoring, all-around quality monitoring cannot be achieved, and a closed-loop processing mechanism is lacked for data quality.

Description

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AI Technical Summary

Benefits of technology

The present technology describes how it can manage large amounts of diverse types of data efficiently by accessing multiple sources at once without compromising their accuracy. It uses various tools such as data readers, probes, resolutions, and filters to retrieve relevant data quickly while maintaining consistency across all these platforms. This allows companies to better analyze complex datasets based on specific attributes like location, productivity, etc., making them easier to operate and improve efficiency.

Problems solved by technology

This patented technical problem addressed by this patents relates to improving the efficiency and effectiveness of integrating large amounts of data across multiple platforms while ensuring consistence within specifications. Existing systems are either poorly integrated or expensive due to their own limitations like communication protocol issues, memory capacity constraints, processor performance limits, and price sensitivity. Additionally, existing processes used for handling data may not provide comprehensive analysis without considering factors that contribute to data qualification.

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