对于业务分析系统，该公司需要基于规范化的数据模型创建多维模型。
For the business analysis system, the company needs to create multidimensional models based on the normalized data model.
规范化数据模型以规范化方式描述业务实体、属性和关系，以反映它们的业务用途。
The canonical data model describes the business entities, attributes, and relationships in a normalized form structured to reflect their business use.
规范化数据模型定义一个组织的信息的结构。
The canonical data model defines the structure of an organization's information.
在随后的SOA项目中，规范化数据模型逐渐加入更多的业务领域和信息类型，使它们也被纳入到组织的SOA的范围。
In subsequent SOA projects, the canonical data model is enhanced to include additional business areas and information types as they come into scope for that organization's SOA.
规范化数据模型为各个服务的消息的信息内容提供一个共同的格式。
A canonical data model provides a common format for the information content of the messages of the individual services.
规范化数据模型是SOA项目中实体及其属性和基于业务需求的关系的一个公共表示。
A canonical data model is a common representation of entities, their attributes and relationships based on the business requirements in the SOA project.
取决于项目的复杂性，可以在两个不同层次的抽象和粒度上指定规范化数据模型。
Depending on the complexity of the project, a canonical data model may be specified at two different levels of abstraction and granularity.
很多公司已经为公司中最重要的实体开发了一个规范化数据模型。
Many companies have already developed a canonical data model for the most important entities across their enterprise.
而且，可以使规范化数据模型遵从通过业务术语表表达的标准化术语。
Furthermore, canonical data models can be made to comply with standardized business terms as expressed through a business glossary.
在SOA项目中，规范化数据模型是增量式地开发的。
The canonical data model is developed incrementally during the SOA project.
现在该企业已经创建了规范化数据模型，除了为交易系统的销售情况建立数据模型之外，还为产品、员工、客户和商店创建数据模型。
Now it has created normalized data models, including products, employees, customers, and stores, in addition to sales for the transaction system.
基于规范化数据模型发现多维信息。
Discovering multidimensional information based on a normalized data model.
规范化决定在逻辑数据模型中得以完成，并导致实体-实体关系与超类型-子类型层次关系的最终规范化表示。
Normalization decisions are finalized in the logical data model resulting in the final normalized representation of entity-to-entity relationships as well as supertype-to-subtype hierarchies.
这是一个迭代的过程，常常需要多次与RationalDataArchitect中的规范化数据模型进行互换。
It is an iterative process that often requires several interchanges with the canonical data model in Rational data Architect.
规范化数据模型到业务流程的集成。
例如，它可以在逻辑模型与物理模型之间映射，也就是规范化数据模型的概念与这些概念在数据平台中的实现之间的映射。
For example, it can map between a logical and physical model, that is, between the concepts of the canonical data model and the realization of these concepts in the data platform.
对于包含SOA项目的相关数据的各个系统，规范化数据模型为关键实体、它们的属性和关系提供一致的定义。
A canonical data model provides a consistent definition of key entities, their attributes and relationships across the various systems that hold relevant data for the SOA project.
规范化数据模型定义业务过程和服务建模所用的数据结构、属性和关系。
The canonical data model defines data structure, attributes and relationships used for business process and service modeling.
规范化数据模型和消息模型的模式将在本系列的后续文章中讨论。
The pattern of a canonical data and message model is presented in a future article in this series.
规范化数据模型在数据层建立这种统一的格式，而规范化消息模型在服务层定义这种统一的格式。
The canonical data model establishes this common format on the data layer while the canonical message model defines this uniform format on the services layer.
例如，如果在数据配置期间发现有隐藏的属性嵌入在文本字符串中，就可以修改规范化数据模型，把它们变成显式的属性。
For example, if hidden attributes are discovered to be embedded in a text string during data profiling, then these can be made explicit in a revised canonical data model.
规范化消息模型最终基于逻辑数据模型和业务术语表，中间要通过一个服务分析模型。
The canonical message model is ultimately based on the logical data model and business glossary, via a service analysis model.
数据类型的这些表达的一致性非常重要，这种一致性是通过指定规范化数据模型取得的。
Consistency across these expressions of data type is critical and is driven through the specification of a canonical data model.
这意味着数据和服务架构师在定义或扩展规范化数据模型和服务模型时，可以直接使用结构化的、一致的业务术语。
This means that data and service architects have direct access to structured and consistent business terms when defining or extending canonical data models and service models.
在很多情况下，规范化数据模型采用信息工程技术，而服务分析模型采用UML技术，业务定义在两者之间可以互换。
In many cases, the canonical data models employ information-engineering techniques and the service analysis models employ UML techniques with business definitions being interchanged between the two.
随着在服务模型中添加更多的细节，开发规范化消息模型，这个模型代表规范化数据模型的物理实例。
As specification detail is added to the service model, you develop the canonical message model which represents the physical instantiation of the canonical data model.
这样产生的规范化数据模型的模型结构可以与SOA项目开发过程中使用的其他工具进行交换。
The resulting model structures of the canonical data model may be interchanged with several other tools used in the development process within an SOA project.
不论出处如何，当术语表模型在RDA 中时，就可以将标准业务术语映射到规范化（概念/逻辑）数据模型的形式化结构。
Regardless of its origin, the presence of a glossary model in RDA enables mapping of standard business terms into the formalized structures of the canonical (conceptual/logical) data model.
这使得表达可重用数据概念的规范化数据模型与其他工件紧密集成，例如业务术语表、服务定义和业务流程。
This allows the canonical data models that express the reusable data concepts to be integrated tightly with other artifacts such as business glossaries, service definitions and business processes.
规范化数据模型的目的不是将数据建模限定在单个的数据库和它的相关物理数据模型上。
The objective is not to limit data modeling to a single database and its related physical data model.
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