Data asset label management system and method

Abstract

The invention relates to a data asset label management system and method, and the system comprises a data resource general protocol adapter which is responsible for the unified butt joint of various data resources and collection; a data resource management module which is responsible for performing unified registration and classification on various data resources acquired by the data resource general protocol adapter; a data asset label management module which is used for pre-defining and self-defining data asset labels and is responsible for grading and classifying the data asset labels; a data asset marking module which is used for marking the classified data resources by adopting data asset labels so as to form data assets; and a data asset maintenance module which is responsible for monitoring and maintaining data assets. The system and method have the advantages of universality, high efficiency and effectiveness, all types of data such as databases, file systems and files can be supported, data assets are produced in the form of data asset labels, it is ensured that valuable data form the data assets, and the whole system can ensure that the data assets are complete and effective.

Description

technical field

[0001] The invention relates to the technical field of big data platform construction and management, including the effective use and maintenance of data assets, and in particular to a data asset tag management system and method. Background technique

[0002] With the development of information technology, data has penetrated into every industry and business function field today, and has become an important factor of production. Effective management of massive data and further mining and application have become a key factor for enterprises to improve their core competitiveness and seize the market. The key to the opportunity; under this background, big data technology has emerged as the times require, which has distinctive characteristics such as large data volume, multiple data types, low value density, and fast processing speed. At present, in the practice of big data construction, the management and application of data assets is still in its infancy, and t...

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