Data asset management method based on big data analysis

Abstract

The invention discloses a big data analysis-based data asset management method. The method comprises the following steps of S1, evaluating data quality, and exploring data content, structure and abnormality; S2, establishing a data quality management policy and defining a target; S3, determining reasons of data quality problems, designing and implementing data quality service rules, and formulating an improvement scheme; S4, forming complete data quality monitoring including prevention control, process control and supervision control mechanisms; S5, regularly carrying out data quality inspection and cleaning work; and S6, comparing the target, monitoring the data quality, continuously monitoring and managing the data quality in the whole business application, archiving and communicating the quality management effect, and obtaining an improvement and an improvement result. By establishing a data quality management policy and perfect data quality monitoring, source data can be strengthened, data processing sticking points can be verified, and data quality can be continuously monitored and managed in the data maintenance and use process.

Description

technical field [0001] The invention relates to the technical field of asset big data management, in particular to a data asset management method based on big data analysis. Background technique [0002] Data asset management is defined as: Data asset management is the set of business functions that plan, control and deliver data and information assets, including the development, execution and monitoring of data-related plans, policies, programs, projects, processes, methods and procedures, thereby Control, secure, deliver and enhance the value of your data assets. [0003] Data asset management is generally considered to have ten major data management functions: data governance, data architecture management, data development, data operations management, data security management, reference data and master data management, data warehouse and business intelligence management, document and content management, Metadata management and data quality management, where there is a di...

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Problems solved by technology

[0004] At present, enterprises do not manage data quality in place, and cannot manage and control data through effective data quality control methods, and cannot eliminate data quality problems to improve the ability of enterprises to realize data. Therefore, we propose a method based on big data analysis. Data asset management method to solve the above problems

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