Using these data sets, we can get the work items and their structures.
使用这些数据集，我们可以得到工作项目和它们的结构。
If you can gather these data, you can then determine those techniques that are most effective in your environment.
如果您可以搜集这些数据，那么您可以确定那些在您的环境中最有效的技术。
OCLC is working to connect these data silos.
OCLC正在努力把这些数据的竖井连接起来。
All these data were used for Google Analytics.
所有这些数据都用于谷歌分析。
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。
The fields hash will allow referring to these data fields by name later in the program.
字段散列允许稍后在程序中按名称引用这些数据字段。
So you don't have to understand the WSDL and create all these data structures from scratch.
所以您不需要了解WSDL并且不用从头开始创建所有这些数据结构。
To access these data stores, you need to create and appropriately configure security realms.
要访问这些数据存储，您需要创建并适当地配置安全领域。
Each of these data sets has specific values, and most of those have their own structures.
其中每种数据集都具有特定的值，绝大多数都有着自己的结构。
If you have ever used another programming language, these data types probably seemed familiar.
如果您曾经使用过其他编程语言，那么对这些数据类型可能不会陌生。
More studies are needed to confirm these findings as these data are from a subgroup analysis.
鉴于以上数据是通过亚组分析所生成，因此我们还需要开展更多的研究来对以上发现作进一步确认。
From these data, the researchers determined each baboon's top three partners in any given year.
无论在哪一年，研究人员都是根据以上数据来确定与每只狒狒关系最密切的三个伙伴。
When users need to analyze or retrieve these data, they must leverage various custom-built tools.
当用户需要分析或者检索这些数据的时候，他们就必须利用各种自定义的工具。
How should I deploy WebSphere Application Server across these data centers for high availability?
是否应该跨这些数据中心部署WebSphereApplicationServer，以获得高可用性？
XQuery Bridges these data warehouses by showing which products cause the most unresolved support calls.
XQuery通过显示哪些产品造成最多未解决的支持电话，建立了这两个数据仓库之间的桥梁。
Figure 2 illustrates examples for each of these data storage options. (View a larger version of Figure 2.)
图2展示了针对这些数据储存选项的例子(查看图2的大图)。
They are linking communications systems to shunt these data to whomever can work them into useful knowledge.
科学家们正在将各个通讯系统连接起来，从而将收集到的数据资料传输给任何可将其转化为有用知识的使用者。
For the performance tests I'll cover in Part 2, I generated code using each of these data binding frameworks.
对于将在第2部分中讨论的性能测试，我用每一种数据绑定框架来生成代码。
None of these data structures includes any form of error-detection capability, so damage can be difficult to spot.
这些数据结构都没有任何形式的错误探测功能，因此，损坏很难定位。
A 'traditional' application would need to maintain tables for each of these data items and enforce integrity rules.
“传统的”应用程序必须要维护存储这些数据项的表并实施完整性约束。
In many cases the federated server needs to compensate for the differences in the implementation of these data sources.
在许多情况下，联邦服务器需要处理这些数据源实现的差异。
Some of these data collectors might require you to answer questions, such as What is the product's installation directory?
有些数据收集器可能要求您回答一些问题，如产品的安装目录是什么？
Consider what happens when Linux wants to read or write one of these data structures on a new disk with 4096-byte sectors.
想一下，当Linux想在一个带4096字节扇区的新磁盘上读写这些数据结构时，会发生什么事情。
If you haven't read Part 1, you may want to refer back to it to learn more about the features of these data binding frameworks.
如果您还未阅读第1部分，您也许应该回头阅读一下那篇文章，以便了解更多有关这些数据绑定框架特性的知识。
You can also place identifiers on a client the first time they connect, and then have these data sent on subsequent connections.
还可以在客户机与远程主机第一次连接时在客户机上放置标识，然后在后继连接上发送这些数据。
By integrating data from various sources, you can discover relationships between these data that are otherwise difficult to find.
通过集成来自不同数据源的数据，就可以发现这些数据之间原本很难发现的关系。
In fact, these data categories are the real thing, and the hierarchy inside each profile is a virtual copy of the same structure.
实际上，这些数据类别是真实的，而配置文件中的结构则是这个结构的虚拟副本。
This means that you can practically write any client that can consume these data and present them to the user in any way you want.
这意味着您可以实际编写任何能够使用这些数据并以您希望的方式向用户显示数据的客户端。
This means that you can practically write any client that can consume these data and present them to the user in any way you want.
这意味着您可以实际编写任何能够使用这些数据并以您希望的方式向用户显示数据的客户端。
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