数据仓库环境通常要定期处理大量数据。
There is often a huge amount of data that needs to be processed regularly in a data warehouse environment.
在数据仓库环境中，元数据互操作性是一个关键问题。
Metadata interoperability is a key problem in data warehouse environment.
在数据仓库环境中，数据只有在组织和显示为信息后才有价值。
In a data warehouse environment, data is only valuable when it is organized and displayed as information.
数据量：对于一个数据仓库环境，常常需要对巨量的数据进行常规性的处理。
Data Volume: There is often a huge amount of data that needs to be processed regularly for a data warehouse environment.
例如，在数据仓库环境中，数据中可能只有少数几个地方做了修改。
For example, in a data warehouse environment, there may be few changes in the data.
设计ETL任务(或数据流)是将XML集成到数据仓库环境的重要方面。
Designing ETL jobs (or data flows) is an important aspect of integrating XML into data warehouse environments.
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。
Part 2 covers additional details related to MQTs, MDCs, and DPF partitioning keys, focusing on the data warehouse environment.
这将为操作节省大量时间，特别是对于通常要广泛使用DGTT的大型数据仓库环境而言。
This will provide significant time savings for operations, especially for large data warehousing environments that typically make extensive use of DGTTs.
DPF对于以读操作为主的工作负载很有用，包括数据仓库环境中常见的工作负载。
DPF can be useful for read-intensive workloads, including those common to data warehouse environments.
在数据仓库环境下，经常会碰到涉及大量数据的复杂查询，包括多表连接、聚集计算等。
Under data warehouse environment, the complex query of the mass data are met frequently, including the multi-tables join, gathers the computation and so on.
Merge在数据仓库环境(etl)中特别有用，将其中的事务表合并到更大的仓库表中。
Merge is especially useful in data warehouse (ETL) environments where transaction tables are merged with bigger warehouse tables.
与数据仓库的分析集成：首先，MDM系统把主数据提供给数据仓库，提高数据仓库环境的精确性。
Analytics integration with data warehouses: First, an MDM System provides master data to the data warehouse for accuracy improvements in the data warehouse environment.
循环日志记录通常在数据仓库环境中使用，在该环境中，恢复数据库需要的只是恢复数据库映象的问题。
Circular logging is typically used in data warehouse environments where the need to recover a database is just a matter of restoring a database image.
数据摄取应用程序设计应该容纳一个活动的数据仓库环境，其中所有工作负载都应该处于在线状态并能并发地运行。
The data ingest application design should accommodate an active warehousing environment where all workloads are intended to run online and concurrently.
请继续关注第 2部分，到时候我们将研究如何在数据仓库环境中使用Design Advisor。
Stay tuned for Part 2, when we’ll look at how to use the Design Advisor in a data warehouse environment.
在典型的数据仓库环境中，最新的数据变化频繁，而历史数据变化相对较小，这使得分区级别的REORG对于针对活动数据的重组尤为重要。
In typical warehouse environments, recent data changes frequently while historical data is more or less static and this makes partition level reorg invaluable for reorganizing only the active data.
在处理像数据仓库环境中数据库那样的巨型数据库方面，Oracle和DB 2都提供了增量和差异备份，避免复制未更改的数据页。
Dealing with huge databases such as those in data warehouse environment, both Oracle and DB2 provide incremental and differential backup to avoid copying unchanged data pages.
最后，对于你们这些搭建了数据仓库的人，详细的矩阵往往是一个有用的工具作为能够证明“作为”一个更成熟的数据仓库环境的标志。
Finally, for those of you with an existing data warehouse, the detailed matrix is often a useful tool to document the "as is" status of a more mature warehouse environment.
研究了聚集查询重写的特征，根据数据仓库环境下聚集查询需要快速计算结果的特点，给出了一个基于聚集查询重写的快速近似计算模型。
This paper researches into the characteristic of aggregate query rewriting and gives a kind of rapidly approximate query computing model based on aggregate query rewriting under the data warehouse.
产品化阶段的目标是成功地将数据仓库部署到生产环境中。
The goal of the Transition phase is to successfully deploy your data warehouse into production.
以下部分描述了OLTP环境中的3个特性；然而，每一个特性也都将提高决策支持和数据仓库系统的性能。
The following sections describe three of these features in an OLTP context; however, each of these features will improve the performance of decision support and data warehouse systems as well.
数据分区提供了许多有用的好处，特别是在数据仓库和决策支持环境中。
Data partitioning provides many useful benefits, particularly when used in data warehouse and decision support environments.
XML使用的增长促使许多公司探索如何将XML运营数据集成到自己的数据仓库和业务智能环境中。
This growing use of XML is prompting many firms to explore how to integrate XML operational data into their data warehouses and business intelligence environments.
您将会看到在移交阶段，怎样有效地将数据仓库部署到产品环境中。
You'll see how the data warehouse is effectively deployed into production during the transition phase.
数据仓库和业务智能化环境的一项常见需求是，维护特定时间段内滚动变化的历史数据。
A frequent requirement for data warehouses and business intelligence environments involves maintaining a rolling history of select data over a given period of time.
理解客户的数据环境是数据仓库项目中最重要的任务之一。
Understanding the customer? S data environment is one of the most important tasks in a data warehouse project.
解决方案部署(Solution deployment)：将新的数据仓库解决方案移至生产环境中。
Solution deployment: The new data warehouse solution moves into a production environment.
将数据仓库部署到生产环境——产品化阶段。
Getting the data warehouse into production — the Transition phase.
特别是数据仓库的环境里，很多的表都是只读的或者是大部分都是读的。
Especially in data warehouse environments, many tables may be read-only or read-mostly.
数据仓库是一种数据环境，是用于信息处理的单一和综合的数据源。
The data warehouse is the data environment that can be used as the single integrated source of data for processing information.
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