大数据应用中的数据分级管理探究

Research on Data Hierarchical Management in Big Data Applications

随着大数据应用的日益广泛,数据信息的管理成为制约大数据发展的关键因素。对数据进行分类分级,能够体系性解决大数据在应用场景中的安全问题,还能够为大数据的持续高速迅猛发展起到重要的保障作用。目前数据分级已经形成了政策层面的顶层设计、应用场景不断扩大。但随着应用场景的不断转变以及提升,数据分级的目标和价值也在不断发生转变,探索新场景下数据分级的属性、具体的分级方法和流程,对于不同场景下大数据应用过程中的数据分级具有重要意义。

With the increasingly widespread application of big data,the management of data information has become a key factor restricting the development of big data.Classifying and grading data can systematically solve the security issues of big data in application scenarios,and also play an important role in ensuring the sustained and rapid development of big data.At present,data classification has formed a top-level design at the policy level and has been widely and deeply applied in application scenarios.However,with the continuous transformation of application scenarios and the goal and value of improving data classification,exploring the attributes,specific classification methods,and processes of data classification in new scenarios is of great significance for data classification in big data application processes in different scenarios.