• Service message model (canonical data models)

    服务消息模型(规范数据模型)

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  • We just went from one version of data models to another.

    我们刚刚从一个版本的数据模型转到另一个版本的数据模型。

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  • RDA can create logical, physical, and domain data models.

    RDA可以创建逻辑、物理和领域数据模型。

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  • The difference is due to different supported data models.

    不同之处在于,有不同的受支持数据模型。

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  • Alternate data models are easily supported, as shown here.

    可以很容易地支持备用数据模型,如下所示。

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  • That has big implications for the design of the data models.

    对于数模型的设计来说这已经产生了重大的影响。

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  • Business names are used in conceptual or logical data models.

    业务名称用在概念性或逻辑数据模型中。

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  • These preferences apply to all data models in your workspace.

    这些首选项应用于您的工作空间中的所有数据模型。

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  • Within your project, navigate to the Data Models folder.

    在项目中,导航到Data Models文件夹。

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  • Messaging between services and data models is closely related.

    服务和数据模型之间的消息传递紧密相关。

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  • Physical data models - Blueprint of your physical tables and columns.

    物理数据模型——物理表和列的蓝图。

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  • In most organizations, these data models are at the enterprise levels.

    在大多数组织中,这些数据模型处于企业级别。

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  • For example, translation systems between data models must be designed.

    例如,我们必须设计数据模型之间的转换系统。

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  • The project needs to consider, at least in part, existing data models.

    项目需要考虑已有的数据模型(至少需要考虑一部分)。

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  • First, we declare two data models instead of one as shown in listing 3.

    首先,我们将声明两个数据模型(而不是一个),如清单3所示。

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  • It can also ease the mapping from business requirements to data models.

    它还可以简化业务需求与数据模型之间的映射。

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  • The data models must have sufficient detail as required by the service.

    数据模型必须具有服务所需的足够的详细信息。

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  • Model (XML) - Well defined API XML resources represent the data models.

    模型(xml)—使用定义良好的API XML资源来表示数据模型。

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  • Data models quickly become very large with many entities and relationships.

    数据模型很快就会变得非常庞大,包含很多实体和关系。

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  • Let me bracket XML for a few moments by talking about abstract data models.

    我先将XML搁置一边来讨论一些抽象的数据模型。

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  • It also helps in synchronization of logical data models and physical models.

    它还有助于实现逻辑数据模型和物理模型的同步。

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  • Physical data models are database specific and represent the database schema.

    物理数据模型是数据库特定的,代表数据库模式。

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  • RDA explicitly supports glossary modeling during the definition of data models.

    rda显式地支持数据模型定义期间的术语表建模。

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  • There is one more thing we need to consider before creating our new data models.

    在创建新数据模型之前,还有一件事需要考虑。

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  • This eventually helps drive the definition of conceptual and logical data models.

    这会帮助驱动概念和逻辑数据模型的定义。

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  • The method described in this tutorial is the IIW roadmap for developing data models.

    本教程中描述的方法是用于开发数据模型的IIW路线图。

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  • You can collect the data models by re-engineering and integrating source data models.

    您可以通过重新构建和集成源数据模型来收集数据模型。

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  • RDA supports the comparison and synchronization of data models across the enterprise.

    RDA支持在企业范围内比较和同步数据模型。

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  • The advanced profile provides the comprehensive details on the process and data models.

    高级配置文件提供了更详细的流程及数据模型的信息。

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  • Logical data models are used for creating the blueprint needed to design your database.

    逻辑数据模型用来创建设计数据库所需的蓝图。

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