• We'll look more closely at the Data Capture environment and discuss the role it plays in a Premises Server EDA model later in this section.

    我们稍后将进一步分析DataCapture环境,并讨论其在PremisesServerEDA模型中扮演的角色。

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  • This tutorial takes a basic approach to working in Data Studio's Eclipse environment, explaining user interface concepts and offering steps for creating connections.

    本教程采用一种基本的方法使用DataStudio的Eclipse环境,同时解释一些用户界面的概念,并逐步讲解如何创建连接。

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  • Following is an outline of the processing flow of the Data Web Service runtime environment shown in Figure 5.

    下面概述图5所示的DataWebServices运行时环境的处理流。

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  • You'll need to tune these scoring parameters for your data environment.

    您需要调整数据环境的这些评分参数。

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  • After collecting business requirements and researching the business and data environment, you can perform gap analysis.

    在收集业务需求并研究业务和数据环境之后,您就可以执行差异分析了。

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  • 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。

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  • This is because most systems in a modern data center environment are dynamic and always under continuous upgrades, improvements, and tuning.

    这是因为现代数据中心环境中的大多数系统是动态的,总是在不断地升级、改进和调优。

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  • Part 2 covers additional details related to MQTs, MDCs, and DPF partitioning keys, focusing on the data warehouse environment.

    第2部分将介绍关于MQT、MDC和DPF分区键的更多细节,重点分析数据仓库环境。

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  • In the Data mining environment, this means to transfer results to the people who benefit the most from the generated business insights.

    在数据挖掘环境中,这意味着将结果传递给最能从生成的业务洞察力中受益的人。

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  • All documentation in a data center environment must be automatically generated on a scheduled basis (hourly, daily, weekly, monthly).

    数据中心环境中的所有文档必须定期地(每小时、每天、每周或每个月)自动生成。

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  • Meeting with customers to collect the customer's business process models, applications, test files, and environment data.

    与客户见面,收集客户的商业过程模型、应用程序、测试文件,和环境数据。

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  • Optim is the family name for a portfolio of products used to deliver a modular, integrated data management environment for managing data across its lifecycle.

    Optim是用于交付模块化集成数据管理环境的产品组合的统一名称。

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  • Contains all the data files of the target environment before import.

    包含目标环境导入前的所有数据文件。

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  • Note that your results might vary significantly based on your specific execution environment and data.

    注意,根据您的特定执行环境和数据的不同,您的结果可能差别很大。

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  • Antipatterns: Manually applying database and data changes in each target environment.

    反模式:在每个目标环境中手动应用数据库和数据更改。

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  • WebSphere eXtreme Scale also provides features to replicate data throughout the environment, further improving resiliency.

    WebSphereeXtremeScale还提供了复制整个环境中的数据的特性,从而进一步提高弹性。

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  • The data problem creates a rigid environment that lacks reuse and prevents agility.

    数据问题导致了缺乏重用并阻碍敏捷性的僵化环境。

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  • Scaling an application involves understanding the flow of data in this tiered environment, and looking for bottlenecks.

    在扩展应用程序的容量时,应该了解数据在分层环境中的流动并寻找出现瓶颈的位置。

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  • Keep in mind that a SaaS product in the cloud has different deployment and usage conditions than a product deployed in a typical data center environment.

    要记住,与部署于典型的数据中心环境中的产品相比,云中的SaaS产品有着不同的部署和使用条件。

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  • WebSphere sensor Events is a collection point for sensor data and an environment for event server processing.

    WebSphereSensorEvents是传感器数据的收集点,也是事件服务器处理的环境。

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  • The information to collect includes external data from the environment as well as internal information fed back from the other parts of the UI.

    要收集的信息包括来自环境的外部数据和从UI的其他部分反馈回来的内部信息。

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  • Mapping lets you add data binding to an existing environment.

    映射允许在现有环境中添加数据绑定。

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  • By default, a Web content management environment stores data files on the file system.

    默认情况下,Web内容管理环境在文件系统中存储数据文件。

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  • The reasons for using a script mechanism, such as mkewuid, to generate EWU values are numerous and important for the operation and management of a modern data center environment.

    使用mkewuid 这样的脚本生成EWU值有许多原因,这对现代数据中心环境的操作和管理非常重要。

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  • A distributed directory is a directory environment in which data is partitioned across multiple directory servers.

    在分布式目录环境中,数据跨多个目录服务器分散存储。

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  • To this snippet we want to add support for the 4th type of logon data, the trusted environment variable, in this example REMOTE_USER.

    我们希望在这段代码中添加对第四类登录数据(可信的环境变量,在此示例中是REMOTE_USER)的支持。

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  • IBM Cognos 8 BI v3 includes best practices in the data modeling environment through a "model Advisor," as well as several enhancements that help ease their tasks and make them more efficient.

    IBMCognos8BIv 3通过“ModelAdvisor”提供数据建模环境中的最佳实践,还通过几项改进帮助简化他们的工作,提高工作效率。

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  • Four Domino partitions were configured for this environment, and data points of 6000 and 9000 users were tested.

    我们为这个环境配置了4个Domino分区,测试的数据点有6000和9000个用户。

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  • During the installation of the test environment, some J2C Authentication data entries were created with a default user.

    在测试环境的安装期间,一些J2C身份验证数据项是使用缺省用户创建的。

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  • First, consider an environment where the data is partitioned into three Apache Derby databases.

    首先,考虑这样一个环境,其中数据被分区到三个ApacheDerby数据库。

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