Metadata interoperability is a key problem in 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。
For example, in a data warehouse environment, there may be few changes in the data.
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。
Stay tuned for Part 2, when we’ll look at how to use the Design Advisor in a data warehouse environment.
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。
There is often a huge amount of data that needs to be processed regularly in a data warehouse environment.
数据仓库环境通常要定期处理大量数据。
In a data warehouse environment, data is only valuable when it is organized and displayed as information.
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。
Data Volume: There is often a huge amount of data that needs to be processed regularly for a data warehouse environment.
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。
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。
Analytics integration with data warehouses: First, an MDM System provides master data to the data warehouse for accuracy improvements in the data warehouse environment.
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。
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.
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。
Of course, in a production environment, operational data and warehouse data would be managed in separate databases, usually on separate servers.
当然，在生产环境中，操作型数据和仓库数据可能在不同的数据库中，通常在不同的服务器上。
Understanding the customer? S data environment is one of the most important tasks in a data warehouse project.
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。
Solution deployment: The new data warehouse solution moves into a production environment.
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。
InfoSphere Warehouse data mining is built with DB2 stored procedures and user-defined functions for high-performance in-database execution, taking advantage of DB2 as an execution environment.
InfoSphereWarehouse数据挖掘是用DB 2存储过程和用户定义函数构建的，以利用DB 2作为执行环境，从而获得高性能的数据库内执行。
Tivoli data Warehouse for storing historical data collected from agents in your environment.
TivoliData Warehouse用于在您的环境中存储从代理收集来的历史数据。
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.
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。
The data warehouse is the data environment that can be used as the single integrated source of data for processing information.
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。
In the ERP environment, establishes Business Intelligence system based on Data Warehouse, is to be the scheme of a kind of effective support decision.
在ERP环境下，建立基于数据仓库技术的商务智能系统是一种行之有效支持决策的方案。
Data warehouse provides a good data environment for Decision Support System (DSS) and On-Line Analytical Processing (OLAP).
数据仓库是企业决策支持系统(DSS)和联机分析处理(OLAP)的数据环境。
Logistics Information Data Warehouse model's successful construction and operation, provides a good analysis environment for Data Mining of the logistics theme.
物流信息数据仓库模型的成功构建和运行，为物流相关主题的数据挖掘提供了一个良好的分析环境。
With the maturity of the data warehouse technology, it is rcasonable and feasible to divide the whole database into two parts: operational environment and analytic environment.
数据仓库技术的逐渐成熟，使得整个系统的数据库可以分为处理环境和分析环境两部分。
In this paper, we discuss the structure of data environment in CIMS based on data warehouse and present a method to design the operationa…
文章讨论了基于数据仓库技术的CIMS 数据环境结构，并提出了根据企业数据模型同时设计数据处理环境和分析环境的方法。
In this paper, we discuss the structure of data environment in CIMS based on data warehouse and present a method to design the operationa…
文章讨论了基于数据仓库技术的CIMS 数据环境结构，并提出了根据企业数据模型同时设计数据处理环境和分析环境的方法。
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