Determines whether linked cubes on other servers can use this cube as a source cube.
确定其它服务器上的链接多维数据集是否可以将此多维数据集用作源数据。
You can then create a new virtual cube which contains the new dimension and the original source cube.
然后您可以创建一个新的虚拟多维数据集，其中包括新建的维度以及原始的源多维数据集。
This cube will contain the source cube this Mining Model is based on as well as the new dimension being created from the Mining Model.
此多维数据集将包含此挖掘模型所基于的源多维数据集，以及用该挖掘模型创建的新维度。
The definition of a source element gets more complicated when the element represents a row in a relational table or a cell in a multidimensional cube.
当元素表示关系表中的一行或多维立方体中的一个单元时，源元素的定义就变得更加复杂。
In order to connect to the data source DB2 Cube Views provided, you must first connect to the underlying relational database.
为了连接已提供的数据源db2CubeViews，首先必须连接底层关系数据库。
In that file you can see the appropriate syntax for data source, Catalog, and Cube for the data source you are concerned with and enter it in the task wizard.
在该文件中您可以看到您关心的数据源的Datasource、Catalog和Cube的适当语法，并将其输入到任务向导中。
Create a cube called HUMANCOST, and choose GBPM4ETL as the relational data source.
创建一个名为HUMANCOST的多维数据集，选择GBPM 4etl作为关系数据源。
When using IBM Cognos BI as a data source for Transformer, the following are some guidelines regarding efficient cube build times.
对于使用IBMCognosBI作为Transformer的数据源的情况，下面是关于高效多位数据集构建时间的一些指南。
Ensure the Oracle Essbase data source that was created is selected, click Next, and then locate and select the desired cube.
确保选中创建的OracleEssbase数据源，单击Next，然后找到并选择所需的多维数据集。
Ensure the IBM Cognos TM1 data source that was created is selected, click Next, and then select the cube for import.
确保选中创建的IBMCognosTM1数据源，单击Next，然后选择要导入的多维数据集。
The shadow field for a light source, called a source radiance field (SRF), records radiance from an illuminant as cube maps at sampled points in its surrounding space.
光源的阴影字段，称为源辐射场(SRF)，记录从光源辐射率作为立方体在其周围的空间中的采样点处的地图。
In detail it includes the optimization of data source, cube, MDX and the adoption of multi-thread technique and the development of intelligent query division.
具体包括数据源、立方体和MDX的优化以及多线程技术的采用和查询智能拆分的开发。
In detail it includes the optimization of data source, cube, MDX and the adoption of multi-thread technique and the development of intelligent query division.
具体包括数据源、立方体和MDX的优化以及多线程技术的采用和查询智能拆分的开发。
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