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目前，广州数据交易所已按照数据资源化、产品化、资产化、资本化的完整链路构建起一套涵盖企业数据资产管理各阶段的实施路径。沈海介绍，首先要引导企业经由数据治理、资源盘点与质量管理，达成数据资源化；继而通过数据合规管理、产权登记及应用场景开发，实现数据产品化；随后借助数据交易与资产入表，完成数据资产化；最终以数据资产投融资等手段，推动数据资本化。他认为，通过产权登记明确数据权属关系，既可增强数据交易可信度，使金融机构在获取和使用数据时更加确信数据的来源和合法性，避免权属纠纷，降低法律风险，也可获得数据产权登记证书，作为企业融资增信的依据，拓宽企业融资渠道，促进数据要素市场的繁荣。

以广州数据交易所为例，在合规保障方面，其建立了数据流通交易全生命周期安全管控制度体系，强化数据安全、产品安全、系统安全、生态安全管控措施，同时搭建起数据交易分级分类标准、数据质量管理、数据资产管理等数据全生命周期安全管理体系。

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分地区来看，各大数据交易机构的金融场景数据产品分别有哪些特征？《报告》统计分析发现，北数所注重数据来源的授权使用；上数所聚焦金融产品应用场景；广数所聚焦数据技术的应用；深数所致力于构建多元场景生态矩阵；贵数所聚焦提供多样化数据服务。

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随着数据资产质押融资的不断发展和完善，将会推动更多企业加强数据资产的管理和运营，这有助于形成更加活跃、高效的数据要素市场，为金融服务创新提供更多的数据资源和动力。

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一方面，依托广东数字政府建设的公共支撑能力，建设了多层次数据要素流通交易平台，为数据交易供需双方提供安全、可信、便利、高效的平台化服务，并深度融合行业平台交易体系，实现了场内场外数据交易的高效协同。

报告指出，尽管在数据要素市场建设初期存在诸多挑战，但通过持续优化和规范运作，各交易机构在深化数据驱动理念方面发挥着不可替代的作用，正逐步提升服务质量和市场适应性，构建高效、透明的数据流通体系贡献力量。相信随着信息透明度的不断提升，数据交易市场将迎来更广阔的发展前景。

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要素密集度描述了数据产品中数据包的“大小”及“纯度”，是最能体现“数据产品”本义的一项指标。各数据交易机构在该项的得分较为均衡且普遍较高。不过，仍然存在一些产品不含有数据或很少含有数据，以及大批同系列产品字段拆分过于分散的情况。从要素密集度指标细分来看，上海数据交易所得分最高。

分地区来看，各大数据交易机构的金融场景数据产品分别有哪些特征？《报告》统计分析发现，北数所注重数据来源的授权使用；上数所聚焦金融产品应用场景；广数所聚焦数据技术的应用；深数所致力于构建多元场景生态矩阵；贵数所聚焦提供多样化数据服务。

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