• Metadata interoperability is a key problem in data warehouse environment.

    数据仓库环境中元数据互操作性一个关键问题

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  • For example, in a data warehouse environment, there may be few changes in the data.

    例如数据仓库环境中,数据可能只有少数几个地方做了修改

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  • 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,到时候我们研究如何数据仓库环境中使用Design Advisor。

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  • There is often a huge amount of data that needs to be processed regularly in a data warehouse environment.

    数据仓库环境通常定期处理大量数据。

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  • In a data warehouse environment, data is only valuable when it is organized and displayed as information.

    数据仓库环境中,数据只有组织显示信息有价值

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  • Data Volume: There is often a huge amount of data that needs to be processed regularly for a data warehouse environment.

    数据对于一个数据仓库环境,常常需要数据进行常规性的处理。

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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MQTMDCDPF分区更多细节重点分析数据仓库环境。

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  • 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.

    数据仓库环境下经常碰到涉及大量数据复杂查询包括连接聚集计算

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  • Analytics integration with data warehouses: First, an MDM System provides master data to the data warehouse for accuracy improvements in the data warehouse environment.

    数据仓库分析集成首先MDM系统数据提供给数据仓库提高数据仓库环境精确性

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  • 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.

    处理数据仓库环境数据库那样巨型数据库方面,OracleDB 2提供了增量差异备份避免复制未更改的数据

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  • Of course, in a production environment, operational data and warehouse data would be managed in separate databases, usually on separate servers.

    当然生产环境中操作型数据仓库数据可能不同数据库中通常不同的服务器上

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  • Understanding the customer? S data environment is one of the most important tasks in a data warehouse project.

    理解客户数据环境数据仓库项目重要任务之一

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  • Solution deployment: The new data warehouse solution moves into a production environment.

    解决方案部署(Solution deployment):新的数据仓库解决方案生产环境中。

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  • 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DB 2存储过程用户定义函数构建的,利用DB 2作为执行环境,从而获得高性能数据库内执行。

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  • Tivoli data Warehouse for storing historical data collected from agents in your environment.

    TivoliData Warehouse用于环境中存储代理收集来历史数据

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  • 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人,详细矩阵往往有用的工具作为能够证明“作为”一个成熟的数据仓库环境的标志。

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  • The data warehouse is the data environment that can be used as the single integrated source of data for processing information.

    数据仓库种数据环境是用于信息处理单一和综合数据源

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  • In the ERP environment, establishes Business Intelligence system based on Data Warehouse, is to be the scheme of a kind of effective support decision.

    ERP环境下建立基于数据仓库技术商务智能系统行之有效支持决策方案

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  • Data warehouse provides a good data environment for Decision Support System (DSS) and On-Line Analytical Processing (OLAP).

    数据仓库企业决策支持系统(DSS)联机分析处理(OLAP)的数据环境

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  • 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成功构建运行物流相关主题数据挖掘提供了一个良好分析环境

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  • 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.

    数据仓库技术逐渐成熟,使得整个系统的数据库可以分为处理环境分析环境部分

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  • In this paper, we discuss the structure of data environment in CIMS based on data warehouse and present a method to design the operationa…

    文章讨论基于数据仓库技术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分析环境的方法

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  • In this paper, we discuss the structure of data environment in CIMS based on data warehouse and present a method to design the operationa…

    文章讨论基于数据仓库技术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分析环境的方法

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