The applications of enterprise data warehouse have increasingly spread aboard and deep.
企业级的数据仓库应用日益广泛。
These are called conforming dimensions, and they are an early step to building an enterprise data warehouse.
这称为符合维度，这是构建企业数据仓库的前期步骤。
They anoint one data warehouse as the system of record or build a new enterprise data warehouse (EDW) from scratch.
企业选择一个数据仓库或者从头创建一个新的企业级数据仓库。
The issue in China Pacific Insurance Company (CPIC) building enterprise data warehouse (EDW) project against the background of the BI system in the meta-data management and application of research.
本课题在中国太平洋保险公司（CPIC）建设企业数据仓库（EDW）的项目背景下对BI系统中的元数据管理和应用作了研究。
This is because it is not always feasible to consolidate enterprise data into a data mart or warehouse.
这是因为，将企业数据合并到专用数据栈或数据仓库之内并不总是可行。
Are you building a data warehouse for the entire enterprise?
您打算为整个企业构建一个数据仓库吗？
For instance, the average enterprise commonly has more than one data warehouse to track and analyze company data.
比如，一般企业通常有多个数据仓库来跟踪和分析公司数据。
The raw data from sensors is useless to enterprise resource planning systems and warehouse management systems and has limited value in driving smarter business processes.
来自传感器的原始数据对企业资源规划系统和仓库管理系统没有任何用处，并且对促成智能业务流程的价值不是很大。
For the purpose of this discussion, let's assume that you're building a data warehouse for the entire enterprise.
出于本文的目的，让我们假设您将为整个企业构建一个数据仓库。
Monitor and analyze multiple DB2 instances running a wide variety of workloads - OLTP, data warehouse, and enterprise content management - all from a single control point.
从单一控制点监视和分析多个运行各种工作负载的DB 2实例—oltp、数据仓库和企业内容管理。
As a result, you benefit from delivering new projects with a much shorter time to market, extending your warehouse with ad-hoc queries, and producing a unified view for your enterprise data.
这样一来，您就可以以更短的上市时间发布新的projesources . cts、用特殊查询扩展数据仓库并为企业数据生成统一的视图。
They could consist of warehouse management systems (WMS), Electronic Data Interchange (EDI), or an enterprise resource planning system.
这些系统可能包含仓库管理系统(WMS)、ElectronicDataInterchange (EDI)或企业资源规划系统。
Take data warehouse as foundation, with the aid of on Line Analytical Processing and data Mining technology, the composition and design of enterprise Decision Support System are put forward.
本文以数据仓库为基础，与目前流行的联机分析处理、数据挖掘等技术相结合，提出了基于此的决策支持系统的设计。
Describes based on the data warehouse technology enterprise measurement project design.
描述了基于数据仓库技术的企业计量方案设计。
How effectively integrates these isomerism data in the data warehouse, is a difficult problem which the enterprise faces.
如何将这些异构的数据有效地集成到数据仓库中，是企业所面临的一个难题。
Data Warehouse is a technology of constructing enterprise information system, which is a new development in recent years, and it can change the collected date into analytical meaningful information.
数据仓库是近年来新兴的一种企业信息系统建设的技术，它能把收集到的数据转变成有意义的可用于分析的信息。
Based on data mining techniques in the data warehouse, this paper discusses how to obtain the information about products and customers effectively for the enterprise decision.
本文基于数据仓库中的数据挖掘技术，针对企业决策问题，讨论了如何有效地获取有关顾客信息及商品信息，以辅助决策者制定决策方案。
To give the enterprise group decision a better support, we put forward a Data Warehouse model (SEGDDWM) for supporting enterprise group decision.
为更好地支持企业群体决策，给出了一种支持企业群体决策数据仓库的模型(SEGDDWM)。
Real-time data warehouse extends the application of traditional data warehouse and can support tactical queries for enterprise.
实时数据仓库扩展了传统数据仓库的适用范围，能给企业提供关于日常战术操作的技术支持。
The warehouse model consists of two parts: storage model for the enterprise to store RFID data on their central server and query model for providing query dataset for specific business units.
本仓储模型包括两个部分：用于企业中心服务器存储基础RFID数据的存储模型和为具体业务部门提供查询数据集的查询模型。
So it is essential to design a high efficiency data warehouse which is suitable to the enterprise according to these features.
因此针对这些特点设计适合企业的高性能数据仓库系统是至关重要的。
Data Warehouse technology is taking the fancy of more and more enterprise because of theme-faced, data integrated, time-related and stability features.
基于数据仓库技术面向主题性、数据集成性、与时间相关和稳定性等特点，越来越受到企业的青睐。
The good combination of data warehouse with data mining technology can effectively perform CRM in enterprise operation.
数据仓库技术与数据挖掘技术有机结合，可以有效地进行企业运作中的客户关系管理。
Arguably the most important type of enterprise database today is called a data warehouse.
如今，最重要的企业数据库是数据仓库。
This paper discusses tools and methods for developing a data warehouse architecture, the layered enterprise model, staged model implementation for strategic information management.
探讨了规划数据仓库体系结构、建立分层的企业级数据模型以及采用分阶段建立模型等方法，解决目前数据仓库开发过程中的问题。
The design of an enterprise financial position analysis and early warning system is put forward after the analysis and justification for the characteristics of the data warehouse.
本文在对数据仓库特征进行分析论证的基础上给出了基于数据仓库的企业财务状况分析预警系统的设计方案。
It provides petroleum enterprise with not only the function of assistant decision by former but also a data warehouse that provides the decision-maker with a strong data-analytic flat.
它不仅为石油企业提供了模型辅助决策的功能，还给决策者提供一个非常强大的数据分析平台——数据仓库。
Finally, from the coal mining enterprise business model, established the data warehouse model, and then design the decision analysis tools based on data warehouse.
最后，从煤矿企业业务模型出发，构建了数据仓库，并讨论了以数据仓库为基础的决策分析工具的开发。
Warehouse data is often gathered from sources throughout an enterprise , including different applications , databases , and computer systems , and is likely to be fragmented and inconsistent.
数据仓库数据经常是从整个企业的各种来源收集的，包括不同的应用、数据库与计算机系统等，因而可能是支离破碎和不一致的。
Reality show that coal enterprise decision support system based on data warehouse provided a strong support for the strategy of coal enterprise production and management.
通过煤矿实际应用表明，数据仓库及决策支持系统的建立为煤矿生产经营管理提供了有力的策略支持。
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