汇总表是创建高性能数据仓库的重要部分。
Summary tables are an important part of creating a high-performance data warehouse.
利用性能数据仓库中的历史数据分析趋势并为增长制定计划。
Leverage historical data in the performance warehouse to analyze trends, and plan for growth.
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。
So it is essential to design a high efficiency data warehouse which is suitable to the enterprise according to these features.
此版本是数据仓库性能和可伸缩性的最终版本。
This edition represents the ultimate in data warehouse performance and scalability.
如果完全可能，初始的大小调整还应调查与填充数据仓库相关的容量和性能方面的情况。
If at all possible, the initial sizing should also investigate volume and performance aspects related to populating the data warehouse.
实际上，MDC是一个能最大化查询性能的特性，对于数据仓库中常用的查询更是如此。
Essentially, MDC is a feature that maximizes performance of queries, especially those commonly found in data warehouses.
在数据仓库活动所用到的顺序存取中，SSD的性能提升没有随机访问那么大。
Sequential access, as exhibited by data warehouse activities, does not produce as great a performance improvement with SSDs as does random access.
在实际的数据仓库中，这样的性能是难以接受的。
This kind of performance is rarely acceptable in the real world of data warehousing.
将所有信用卡事务数据——当前的和过期的、核心的和相关的——存储在数据仓库中会对性能造成负面影响。
Storing all credit card transaction data -- current and outdated, core and related -- in the warehouse negatively impacts the performance.
相比在扩展一个系统时“通过硬件解决问题”，TwinFin旨在从头到尾实现平衡，为数据仓库和分析应用程序提供可扩展性能。
Rather than "throwing hardware at the problem" of scaling a system, TwinFin is designed in-balance from the ground up to provide scalable performance for data warehouse and analytics applications.
以下部分描述了OLTP环境中的3个特性；然而，每一个特性也都将提高决策支持和数据仓库系统的性能。
The following sections describe three of these features in an OLTP context; however, each of these features will improve the performance of decision support and data warehouse systems as well.
对于数据仓库中各种具有不同特征的工作负载的性能。
Performance across the wide range of workload characteristics found in data warehouses.
数据聚簇对于数据仓库查询性能的影响尤其显著，因为常常在一个查询中获取许多行。
Data clustering can have an especially large impact on data warehouse query performance, because rows are often retrieved in large Numbers.
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.
您肯定不希望（或无法等待）将性能数据移动到数据仓库，然后再对它运行查询和分析。
You would prefer not to (or can't wait to) move performance data to a data warehouse and run queries and analytics against it.
数据仓库数据库设计的重点在于查询性能。
The design of a data warehouse database is focused on query performance.
这样的性能可以改进客户的数据仓库建设过程，提高他们的生产率。
This kind of performance can improve the customer's data warehousing process and increase their productivity.
新特性增强了OLTP数据安全性、OLTP性能、数据仓库性能和管理。
New features enhance OLTP data security, OLTP performance, data warehouse performance, and administration.
InformixWarehouseAccelerator提高了我们可以得到的性能水平以及我们期待从数据仓库中获得的性能水平。
The Informix warehouse Accelerator really raises the performance level that we can get and expect from a data warehouse.
IWA是一个令人振奋的突破，它将新的数据仓库技术和传统的Informix关系数据库服务器相结合，产生一种非常快的性能。
IWA is an exciting breakthrough-combining new data warehouse technology with traditional Informix relational database servers-that results in very fast performance.
现在我们来看看在评价和使用这些特性时关键的考虑角度：性能，尤其是通常的数据仓库业务的用户查询的性能。
We now turn to the first key consideration in evaluating and using these features: performance, specifically, performance of typical warehouse business user queries. These queries tend to.
数据建模。数据模型是数据仓库系统的核心部分，它的好坏直接影响到系统的应用效果以及未来扩展性能。
The data model is the nuclear part of the data warehouse system, its quality influences the systematic application result directly and expands performance in the future.
在分布式数据库和数据仓库中，普遍采用数据复制的方法来提高数据的可用性和系统的性能。
To improve data availability and system performance, data replication methods are widely adopted in distributed databases and data warehouses.
史蒂夫康韦，IDC公司研究分析副总经理，专门研究高性能计算（HPC），他说IBM的数据仓库明显比以前的存储系统大。
Steve Conway, a vice president of research with the analyst firm IDC who specializes in high-performance computing (HPC), says IBM's repository is significantly bigger than previous storage systems.
数据复制是分布式数据库和数据仓库中常用的方法，以提高数据的可用性和系统的性能。
To improve data availability and system performance, data replication methods are widely adopted in distributed databases and data warehouses.
本文提出了可用于提高数据仓库性能的两种方法，即非规格化和建立索引，并简单叙述了它们的使用技巧。
The paper shows two methods, indexing and non-standardizing, for creating a high performance warehouse, and the use of these methods.
因此，提高联机分析处理的查询性能就成为了数据仓库领域的关键问题。
Therefore, improving the OLAP query performance becomes the key issue in the field of data warehouse.
性能属性在保证数据仓库模型建设和数据仓库系统建设的质量中扮演关键角色。
Performance property plays a vital role in guaranteeing the quality of data warehouse information model and system design.
它不但可以有效地支持数据仓库上的大数据量批量追加更新，而且具有很高的区域查询性能。
Experimental results show that not only can CMD-Forest support bulk appending efficiently but also provide higher range query performance.
根据使用数据仓库用户群的特点，分析和探讨了提高数据仓库性能的几种途径和方法。
According to the characteristics of data warehouse users, analyses and discusses a few approaches and techniques in order to effectively enhance and improve data warehouse performance.
应用推荐