概述 数据产品这一主题在整个行业中持续受到关注，一些行业引领潮流，而另一些行业则退后一步，吸取其他行业的教训。"数据 产品"已成为一个普遍使用的术语，但其 定义在业内却存在显著差异 。 尽管对于数据产品的构成存在多种观点，但本文提出了一个实用的框架，用于从基础方法到分析方法对数据产品进行全面审 视。 根据我作为顾问的经验，谈话很容易陷入细节，所以我试图将数据产品的概念以及衡量它们如何创造价值的方法，构建成一 个简单的结构，然后可以应用并进一步扩展。 需要记住的是，数据产品组织的目标不仅是构建数据产品，还要 衡量、管理和理解数据产品…… 他们的数据产品组合是如何被用于实现主要业务目标的 。 一 数据产品谱系 例如，"客户 360"数据产品可能会将客户主数据与交易历史、产品持有情况和互动数据合并。 1.基础数据产品 数据产品体系的最底层是基础数据产品——企业数据架构的基石。这些面向领域的数据产品是主数据和参考数据的权威来 源。 想象一下金融机构的客户主数据产品，其中包含客户信息的黄金来源；或者产品主数据，维护着明确的产品规格和层级结 构。 这些基础产品通过数据市场（即内部平台，可在整个组织内控制数据产品的发现、访 ...

Core Insights - The article discusses the confusion surrounding the term "data owner" in data management and governance, highlighting the importance of clearly defining ownership roles to avoid overlapping responsibilities and inefficiencies in decision-making [1][2]. Group 1: Types of Owners - Business Process Owners are responsible for the overall performance, compliance, and improvement of specific business processes, ensuring data quality and governance standards are met [4]. - System Owners manage the operation, performance, and compliance of specific applications or platforms, implementing technical controls to support governance policies [5][6]. - Data Product Owners focus on delivering and improving data products to meet business and user needs, ensuring the products are valuable and compliant with governance requirements [8][9]. - Data Owners ensure the quality, compliance, and proper use of defined data sets, managing policies and standards related to data creation, maintenance, and sharing [10][11]. Group 2: Application of Ownership Roles - A practical example illustrates the roles of Business Process Owners, System Owners, Data Product Owners, and Data Owners in managing customer data through a CRM system and a Customer 360 platform [12][14][16][18]. - The clear delineation of responsibilities among these roles enhances data governance and ensures that data is effectively managed and utilized [24]. Group 3: Common Misunderstandings - There is often confusion between the roles of Data Owners and Data Administrators, with the former holding decision-making authority and the latter focusing on execution and monitoring [21][22]. - The distinction between systems and products is crucial, as systems are technical platforms while products are services that provide value through data [23]. Group 4: Conclusion - Clearly defined responsibilities are essential for effective data governance, enabling organizations to manage data efficiently and create value [24][25].