Create conceptual data model and information architecture.
创建概念数据模型和信息架构。
Business entities are the fundamental building block of the conceptual data model.
业务实体是概念数据模型的基本构建块。
A conceptual data model is a canonical data model viewed at the highest level of abstraction.
概念数据模型是从最高层抽象看到的规范化数据模型。
This conceptual data model is the basis for both current and future phases of data warehouse development.
这个概念数据模型是当前和将来数据仓库开发阶段的基础。
All you need to do is to generate the physical data model that corresponds to your conceptual data model.
唯一还需要做的事情就是生成与概念数据模型相对应的物理数据模型。
There also is evidence that no one ever produced a reliable conceptual data model. The problem commonly occurs.
有证据显示，没有人建立过可靠的概念数据模型，这是个经常发生的问题。
While not always a part of the conceptual data model, a few major attributes may be defined for illustration purposes.
为了便于演示，可以定义一些主要的属性，不过概念数据模型中不一定非得这样。
The conceptual data model defines the major business entities, generalizations of those entities, and relationships between the entities.
概念数据模型定义主要的业务实体、这些实体的泛化（generalization）以及实体之间的关系。
The conceptual data model is created during the initial phases and typically includes only entities and their most important relationships.
概念数据模型是在初始阶段创建的，通常只包括实体和它们最重要的关系。
The conceptual data model typically is coarse-grained and is intended to show the broad set of entities and relationships under consideration.
概念数据模型通常是粗粒度的，其目的是显示所考虑的宽泛的实体和关系。
Sometimes, relationships expressed during conceptual data modeling (in particular many-to-many relationships) are shown in the logical model as entities themselves.
有时候，概念数据建模期间表达的关系（特别是多对多关系）在逻辑模型中被显示为实体本身。
Conceptual data modeling drives the initial broad specification within the canonical data model, and logical data modeling adds further detail within that same model.
概念化数据建模驱动规范化数据模型中最初宽度的规范，而逻辑数据建模则在同一个模型中增加进一步的细节。
The development of a conceptual data model has several purposes within the SOA project. The main reasons for developing a conceptual data model in the SOA project are.
在SOA项目中，概念数据模型的开发几个目的。
The Entity data model (EDM) is a conceptual data model that can be used to model the data of a particular domain so that applications can interact with data as entities or objects.
实体数据模型(EDM)是一种概念数据模型，能被用来对特定的领域进行数据建模。因此应用程序能和作为实体或对向的数据相匹配。
Unlike the conceptual data modeling phase, where a few attributes may be shown for illustration purposes only, all of the attributes for each entity must be included during logical data modeling.
在概念数据建模阶段，只显示一些作为演示的属性，而在逻辑数据建模期间，必须将每个实体的所有属性包括进来。
Compared with several other data models used in early and recent GIS, the author gives his own idea of what is a geographical space, and then puts forward a new object-oriented conceptual data model.
本文在分析和总结了早期和近期GIS几种数据模型的优缺点的基础上，对地理空间进行了重新理解，给出了一个面向对象的概念数据模型。
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。
It enables developers to query and manipulate data using a conceptual model instead of a physical storage model.
它支持开发人员使用概念模型查询和操作数据，而无需使用物理存储模型。
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。
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.
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。
When you have to change the conceptual or logical data model, you can easily recreate the dependent models and have all your JPA entities in sync.
在不得不修改概念性或逻辑数据模型时，可以轻松地重新创建依赖的模型，让所有JPA实体保持同步。
The data architecture includes conceptual, logical and physical data models and its metadata models.
数据架构包括概念、逻辑和物理数据模型及其元数据模型。
These tend to be more useful for finding highly structured data than for identifying conceptual contents.
这种方法更有利于查找高度结构化的数据，而不适合识别概念化的内容。
Be prepared to make quick decisions, but have the driver of the decision be in-market data, not conceptual analysis.
准备迅速作出决定，但决定必须依据市场数据，而不是概念分析。
While conceptual and logical data modeling may result in two separate yet related data models, more often, these are two sequential phases of analysis acting upon the same data model.
虽然概念数据建模和逻辑数据建模会产生两个不同但是相关的数据模型，但更常见的是，它们是在同一个数据模型上进行的两个连续分析阶段。
For the conceptual form, describe the data rather than using specific values.
所谓概念形态，就是不以特定的值来描述数据。
After the conceptual schema comes the logical schema — the data model that defines the concepts with greater detail and shows the relationships between the entities.
在概念模式后出现的是逻辑模式——用更多的细节定义概念，并显示实体之间的关系的数据模型。
Logical tiers divide the conceptual architecture into components that play specific roles within the application, such as presentation, application logic, business processes, and data access.
逻辑层将概念体系结构划分为在应用程序内扮演特定角色的组件，如表示层、应用程序逻辑层、业务流程层和数据访问层。
These subject areas can be the basis for logically partitioning the data warehouse in several different (conceptual or even physical) databases.
这些主题领域可以是将数据仓库逻辑划分成几个不同（概念的，甚至或者是物理的）数据库的基础。
There are three levels of data modeling: conceptual, logical, and physical.
数据建模有三层：概念、逻辑和物理。
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