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Published: 04 July 2023



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  • 在中国,数据、分析和AI用例的不断扩展,以及数据安全法规的迅速演变,使企业机构的数据管理原则充满不确定性。多数本地数据和分析(D&A)领导者是在被动响应这种快速变化的环境。

  • 中国企业机构对D&A架构的自动化互操作性提出了更高的要求,但拥有主动元数据和知识图谱等必要技术的本土D&A供应商非常有限,导致数据编织的概念和成功实践之间存在差距。

  • 低效的跨部门沟通,依然是企业机构从D&A投资中获得持久业务价值的主要障碍。使用元数据改善IT与业务沟通质量的企业机构,能显著提高分析效率。



  • 针对最常用的数据管理组件,启动数据编织设计实践(从主动元数据和知识图谱开始),并对投资重点(例如数据安全、数据整合、分析民主化)进行优先级排序。

  • 在选择D&A厂商时,优先考虑生态系统参与和自动化能力,为此需要评估厂商如何利用内外部元数据实现与相邻应用的互操作自动化。

  • 持续分析运营元数据和社会元数据,减少在识别“数据设计”和“数据实践”差异方面跨部门沟通的延迟。

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Xingyu Gu Julian Sun Tong Zhang

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