数据仓库的设计，多个维度或一个维度的属性？
Data warehouse design, multiple dimensions or one dimension with attributes?
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。
Stay tuned for the next article in this series, which covers the data warehouse design and implementation stages.
文中详细介绍了该数据仓库的设计模型、结构以及实施原则，并对其应用前景做了展望。
It illustrates the design model, structure and the implementing principle of data warehouse in detail. Finally the prospect of its application is predicted.
第三部分论述了系统数据仓库的设计，包括数据模型的建立，数据的抽取，以及数据管理。
Part three discussed the design of data warehouse, which included the construction of data model, data extract and data management.
论文从概念、逻辑、物理层次进行了数据模型和粒度模型的设计，基本完成了数据仓库的设计。
The paper from the concept, the logic, the physical level has carried on the model design of the data model and the granularity model, basically has completed the data warehouse design.
通过对中邮物流的业务现状分析，提出了中邮物流经营分析系统的总体设计、数据仓库的设计思路；
Through analysis of China Post Logistics' operation, it proposes the system and data warehouse design of "China Post Logistics Management And Analysis System".
最后，以浙江省暂住人口信息系统为背景，按照数据仓库的设计方法，构建了雪花型的暂住人口数据仓库。
At last, according to the design method of DW, in actual application of Zhejiang Province floating population information system, we establish DW of the snow flake schema.
如果它们太具体，就可以能影响数据仓库的设计方式，可能排除看似无关但可能对于所执行的分析十分关键的因素。
If they are too specific, they may influence the way the data warehouse is designed, to the point of excluding factors that seem irrelevant but may be key to the analysis being conducted.
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。
The gap analysis is important, because it is the basis for your data warehouse project proposal and design.
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。
In fact, I see IWA replacing the need for many of the summary tables I design in a data warehouse.
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。
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.
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, two keys to a valuable data warehouse are its flexibility and its ability to handle queries that are unknown at design time.
设计维度数据仓库是一个复杂主题，这三篇文章只触及到它的皮毛。
Designing a dimensional data warehouse is a complex subject, and I have just touched the surface of it in these three articles.
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。
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.
Design Advisor 非常适合为数据仓库优化数据库设计，因为除了关于索引的建议之外，它还可以提供关于MQT、MDC和DPF分区键的建议。
The Design Advisor is well suited for optimizing database design for data warehouses as it provides advice on MQTs, MDCs, and DPF partitioning keys in addition to indexes.
根据定义，数据市场是数据仓库的一个子集，是专门针对特定的用户群或特定的主题领域设计的。
By definition, a data mart is a subset of a data warehouse designed for a specific group of users or a particular subject area.
一个设计良好的数据仓库拥有由大量汇总表，形成一个“金字塔”，每个汇总表都包含更多细节，直到金字塔底部的事实表。
A well-designed data warehouse has a pyramid of summary tables, each one containing more detail until you arrive at the fact table, at the bottom of the pyramid.
在构建比较时匹配粒度级别是数据仓库设计中的关键概念。
Matching up grain levels when building comparisons is a critical concept in designing a data warehouse.
在数据仓库中，事实表或历史表的大小是摆在设计人员和管理员面前的一个挑战。
In data warehouses, the size of fact tables or history tables poses challenges to designers and administrators.
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。
When you use data models to capture business requirements, you are already doing some part of the data warehouse design work.
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 data warehouse architect, who is the key person in data discovery and data warehouse design.
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。
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.
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.
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。
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.
一个成功的数据仓库解决方案的基础就是灵活的设计，这种设计可以适应不断变化的业务数据。
The basis of a successful data warehousing solution is a flexible design which can adapt to changing business data.
数据仓库是为存储集成的业务范围的历史数据而设计的。
A data warehouse is designed for storing integrated business-wide historical data.
数据仓库设计和数据建模是计算机科学和IT结合的产物，众所周知、意义重大。
Data warehousing design and data modeling is a well-known, significant blend of computer science and IT.
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。
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。
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.
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