摘要:随着信息技术的普及，人类产生的数据量正在以指数级的速度增长，如此海量的数据就要求利用新的方法来管理.数据治理是将一个机构（企业或政府部门）的数据作为战略资产来管理，需要从数据收集到处理应用的一套管理机制，以期提高数据质量，实现广泛的数据共享，最终实现数据价值最大化.目前，各行各业对大数据的研究比较火热，但对于大数据治理的研究还处于起步阶段，一个组织的正确决策离不开良好的数据治理.首先介绍数据治理和大数据治理的概念、发展以及应用的必要性；其次，对已有的数据治理技术——数据规范、数据清洗、数据交换和数据集成进行具体的分析，并介绍了数据治理成熟度和数据治理框架设计；在此基础上，提出了大数据HAO治理模型.该模型以支持人类智能（HI）、人工智能（AI）和组织智能（OI）的三者协同为目标，再以公安的数据治理为例介绍HAO治理的应用；最后是对数据治理的总结和展望.



Abstract:Along with the pervasiveness of information technology, the amount of data generated by human beings is growing at an exponential rate. Such massive data requires management with new methodologies. Data governance is the management of data for an organization (enterprise or government) as a strategic asset, from the collection of data to a set of management mechanisms for processing and applications, aiming to improve data quality, achieve a wide range of data sharing, and ultimately maximize the data value. Research and development on big data is nowadays popular in various domains, but big data governance is still in its infancy, and the decision-making of an organization cannot be separated from excellent data governance. This paper first introduces the concepts, developments, and necessity of data governance and big data governance, then analyzes existing data governance technologies-data specification, data cleaning, data exchange, and data integration, and also discusses the maturity measurement and framework design of data governance. Based on these introductions, analyses and reviews, the paper puts forward a "HAO governance" model for big data governance, which aims to facilitate HAO Intelligence with human intelligence (HI), artificial intelligence (AI), and organizational intelligence (OI), and then instantiates the "HAO governance" model with public security data governance as an example. Finally, the paper summarizes data governance with its challenges and opportunities.



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