Analyze transformed dimensional physical data model.
分析转换后的多维物理数据模型。
Model - Supporting conceptual, logical, and physical data modeling.
模型(Model)-支持概念、逻辑和物理数据模型。
Physical data models - Blueprint of your physical tables and columns.
物理数据模型——物理表和列的蓝图。
Visualize - Supporting conceptual, logical, and physical data modeling.
可视化(Visualize)-支持概念数据建模、逻辑数据建模和物理数据建模。
Realization relationships between the different physical data structures.
不同物理数据结构之间的实现关系。
It could outlive many applications, processes, and physical data sources.
它可以比众多应用程序、流程和物理数据源的存在时间更长。
Logical data modeling or physical data modeling and everything in between.
逻辑数据建模或物理数据建模以及两者之间的所有东西。
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。
Transforming the dimensional physical data model to a Cubing or Cognos model.
将多维物理数据模型转换为Cubing或Cognos模型。
Transforming the dimensional logical data model to dimensional physical data model
将多维逻辑数据模型转换为多维物理数据模型
DB2's optimizer is the component that accomplishes this physical data independence.
DB2的优化器是完成该物理数据独立性的组件。
Programmatically traverse and modify IDA logical data model and physical data model.
编程序地遍历和修改rda逻辑数据模型和物理数据模型。
You can also take a logical data model and transform that into a physical data model.
还可以把逻辑数据模型转换为物理数据模型。
Buffer Cache - Memory allocated for storing data blocks read from physical data files.
缓冲区缓存——为存储从物理数据文件读取的数据块而分配的内存。
Transform de-normalized dimensional logical data model to dimensional physical data model.
将非标准化多维逻辑数据模型转换为多维物理数据模型。
The discovery allows users to analyze the objects that are part of the physical data model.
发现了现有数据库之后，用户可以对作为物理数据模型的一部分的对象进行分析。
Contiguity of physical data or keys is important to the speed of table scans or key-index scans.
物理数据或键的连续性对于表扫描或键-索引扫描的速度十分重要。
You have so far seen the concept of logical data models, domain models, and physical data models.
到目前为止，已经介绍了逻辑数据模型、领域模型和物理数据模型的概念。
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。
Now look at how you can change your physical data model and create DDL from the physical data model.
现在看看如何修改物理数据模型，并从物理数据模型创建DDL。
RDA also supports visualization of deployed databases through the extraction of physical data models.
RDA还通过物理数据模型的摘录支持被部署的数据库的可视化。
The objective is not to limit data modeling to a single database and its related physical data model.
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。
Look at how to create a physical data model if you have a logical data model that is already defined.
我们看看在已经定义了逻辑数据模型的情况下，如何创建物理数据模型。
Generation to physical data retains glossary classifications, ready for publication to metadata server.
物理数据模型的生成也保留术语表分类，准备好发布到元数据服务器。
The data architect can then associate these atomic domains to physical columns in the physical data model.
接下来，数据架构师将这些原子域与物理模型中的物理列关联起来。
Developers using ODS can then associate this physical data model with their individual database connections.
然后，开发人员可以使用ODS将这个物理数据模型与他们的数据库连接关联起来。
The physical data model is tightly related to the database system and data warehouse tools that you will use.
物理数据模型是与数据库系统以及您将使用的数据仓库工具紧密相关的。
This separation of access criteria from physical storage characteristics is called physical data independence.
从物理存储特征中分离出访问标准叫作物理数据独立性。
Generation to physical data model also retains glossary classifications, ready for publication to metadata server.
物理数据模型的生成也保留术语表分类，准备好发布到元数据服务器。
As mentioned before, the logical and physical data models are not automatically updated when you change one of them.
如前所述，当更改逻辑数据模型或物理数据模型时，它们中的另一方并不会自动更新。
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