Give a more detailed interpretation of data warehouse theory, development trend and association technique which design data warehouse. There are differences between data warehouse and DBS.
详细解释了数据仓库所涉及的理论、发展趋势以及实现数据仓库的相关技术，从而有区别于DBS的理论、应用等。
Stay tuned for the next article in this series, which covers the data warehouse design and implementation stages.
继续本系列中的下一篇文章，其中将介绍数据仓库的设计和实现阶段。
Each level of data modeling has its own purpose in data warehouse design.
在数据仓库的设计中，数据建模的每一层都有自己的目的。
Domain experts, who provide business domain knowledge for the data warehouse design.
领域专家，为数据仓库设计提供业务领域知识。
The gap analysis is important, because it is the basis for your data warehouse project proposal and design.
差异分析十分重要，因为它是您数据仓库项目建议和设计的基础。
In fact, I see IWA replacing the need for many of the summary tables I design in a data warehouse.
事实上，我们已经看到，IWA取代了我在数据仓库中设计的汇总表中的许多需求。
However, two keys to a valuable data warehouse are its flexibility and its ability to handle queries that are unknown at design time.
然而，有价值的数据仓库的两个关键就是其灵活性以及处理设计时未知的查询的能力。
However, keep in mind that high-level data warehouse design should include all business subject areas.
然而，请记住高级数据仓库设计应该包括所有的业务主题领域。
There are many topics not covered here that are also fundamental in delivering a good data warehouse solution, including system and database design, administration, performance tuning, and others.
有许多主题未在本文中进行介绍，但它们同样是交付良好数据仓库解决方案的基础，包括系统和数据库设计、管理、性能调优等。
When you use data models to capture business requirements, you are already doing some part of the data warehouse design work.
当使用数据模型捕获业务需求时，您就已经完成了数据仓库设计中的部分工作。
However, the formal data warehouse design should begin with data warehouse architecture.
然而，正式的数据仓库设计应该从数据仓库的架构开始。
The design of a data warehouse database is focused on query performance.
数据仓库数据库设计的重点在于查询性能。
You'll learn more about the operational data and the data warehouse design shortly.
稍后您将了解更多关于操作型数据和数据仓库设计的信息。
This does not mean that a more business-wide data warehouse design will not be developed; it will be built incrementally as initial data warehouse implementations expand.
这并不意味着不会开发更大业务范围的数据仓库设计；随着初始数据仓库实现的扩展，将逐渐增加对它的构建。
A data warehouse architect, who is the key person in data discovery and data warehouse design.
数据仓库架构师，是数据发现和数据仓库设计中的关键人物。
A bottom-up implementation involves the planning and design of a data warehouse without waiting for a more business-wide data warehouse design to be put in place.
自底向上的实现包含数据仓库的计划和设计，无需等待安置好更大业务范围的数据仓库设计。
You'll learn more about the operational data and the data warehouse design as you step through each scenario.
学习这些场景时，您将更多地了解运营数据和数据仓库设计。
The selection of an implementation approach is a very important part of data warehouse design; the decision needs to be made at an early stage of the data warehouse project.
实现方法的选择是数据仓库设计中的重要部分；该决策需要在数据仓库项目的早期阶段做出。
Informix 11.7 also has a number of exciting new features for data warehouse design and development that we are still testing, using several very complex queries.
Informix 11.7也有许多令人兴奋的特性，用于数据仓库设计和开发，我们仍然使用几个非常复杂的查询进行测试。
The benefits of two-tier data warehouse design include.
两层数据仓库设计的好处包括。
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。
As a component of InfoSphere Warehouse, Cubing Services provide all the tools you need to design, deploy, and administer a multidimensional model of your relational data.
作为InfoSphereWarehouse的一个组件，CubingServices提供设计、部署和管理关系数据的多维度模型所需的所有工具。
This article focuses on the effective use of the Design Advisor in the context of data warehouse (DW) databases.
本文关注的是如何在数据仓库(DW)数据库方面有效地使用Design Advisor。
You'll use Design Studio to extract data stored in one DB2 XML column and map this data to two tables in a DB2 data warehouse, as shown in Figure 2.
您将使用DesignStudio提取一个DB 2xml列中存储的数据，并将该数据映射到一个DB 2数据仓库中的两个表中，如图2所示。
You can use Design Studio's data modeling wizards to create this table (as well as the data warehouse target tables).
可以使用DesignStudio的数据建模向导创建这个表(以及数据仓库目标表)。
The scenario described in this article uses operational data stored in DB2 pureXML as input to the extract, transform, and load (ETL) job that you'll design to populate a DB2-based data warehouse.
本文描述的场景使用DB2pureXML中存储的操作型数据作为提取、转换和装载（ETL）任务的输入， 这些任务用于填充一个基于DB2 的数据仓库。
InfoSphere Warehouse design Studio is the Eclipse-based tooling platform used to design workload rules, data transformation flows, and analytical flows for data mining and text analytics.
InfoSphere Warehouse DesignStudio是基于Eclipse的工具平台，用于为数据挖掘和文本分析设计工作负载规则、数据转换流和分析流。
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。
This paper discusses main techniques in data warehouse design and management, such as data model, metadata, granularity, data segmentation, data integrating, distributed data warehouse.
本文简要讨论有关数据仓库的主要设计技术与管理技术，包括数据模型、元数据、粒度、数据分割、数据集成以及分布式数据仓库等。
It introduced a design and implementation of a CASE tool used in the database and data warehouse modeling.
介绍了一个可用于数据库和数据仓库建模的CASE工具的设计与实现。
应用推荐