数据库的新应用------毕业设计外文翻译(外文原文+中文翻译).doc
约5页DOC格式手机打开展开
数据库的新应用------毕业设计外文翻译(外文原文+中文翻译),relational databases have been in use for over two decades. a large portion of the applications of relational databases have been in the commercial world, suppo...
内容介绍
此文档由会员 wanli1988go 发布
Relational databases have been in use for over two decades. A large portion of the applications of relational databases have been in the commercial world, supporting such tasks as transaction processing for banks and stock exchanges, sales and reservations for a variety of businesses, and inventory and payroll for almost of all companies. We study several new applications, which have become increasingly important in recent years.
First. Decision-support system
As the online availability of data has grown, businesses have begun to exploit the available data to make better decisions about increase sales. We can extract much information for decision support by using simple SQL queries. Recently however, people have felt the need for better decision support based on data analysis and data mining, or knowledge discovery, using data from a variety of sources.
Database applications can be broadly classified into transaction processing and decision support. Transaction-processing systems are widely used today, and companies have accumulated a vast amount of information generated by these systems.
The term data mining refers loosely to finding relevant information, or “discovering knowledge,” from a large volume of data. Like knowledge discovery in artificial intelligence, data mining attempts to
我们使用关系数据库已经有20多年了，关系数据库应用中有很大一部分都用于商业领域支持诸如银行和证券交易所的事务处理、各种业务的销售和预约，以及几乎所有公司都需要的财产目录和工资单管理。下面我们要研究几个新的应用，近年来它们变得越来越重要。
1、决策支持系统
由于越来越多的数据可联机获得，企业已开始利用这些可获得的数据来对自己的行动做出更好的决策，比如进什么货，以及如何最好的吸引顾客以提高销售额。我们可以通过使用简单的SQL查询语句提供大量用于决策支持的信息。但是，人们最近感到需要使用多种数据源的数据，以便在数据分析和数据挖掘（或知识发现）的基础上，更好的来做决策支持。
数据库应用从广义上可分为事务处理和决策支持两类。事务处理系统现在正被广泛使用，并且公司已经积累了大量由这类系统产生的信息。
数据挖掘这个概念广义上讲是指从大量数据中发现有关信息，或“发现知识”。与人工智能中的知识发现类似，数据挖掘试图自动从数据中发现统计规则和模式。但是，数
First. Decision-support system
As the online availability of data has grown, businesses have begun to exploit the available data to make better decisions about increase sales. We can extract much information for decision support by using simple SQL queries. Recently however, people have felt the need for better decision support based on data analysis and data mining, or knowledge discovery, using data from a variety of sources.
Database applications can be broadly classified into transaction processing and decision support. Transaction-processing systems are widely used today, and companies have accumulated a vast amount of information generated by these systems.
The term data mining refers loosely to finding relevant information, or “discovering knowledge,” from a large volume of data. Like knowledge discovery in artificial intelligence, data mining attempts to
我们使用关系数据库已经有20多年了，关系数据库应用中有很大一部分都用于商业领域支持诸如银行和证券交易所的事务处理、各种业务的销售和预约，以及几乎所有公司都需要的财产目录和工资单管理。下面我们要研究几个新的应用，近年来它们变得越来越重要。
1、决策支持系统
由于越来越多的数据可联机获得，企业已开始利用这些可获得的数据来对自己的行动做出更好的决策，比如进什么货，以及如何最好的吸引顾客以提高销售额。我们可以通过使用简单的SQL查询语句提供大量用于决策支持的信息。但是，人们最近感到需要使用多种数据源的数据，以便在数据分析和数据挖掘（或知识发现）的基础上，更好的来做决策支持。
数据库应用从广义上可分为事务处理和决策支持两类。事务处理系统现在正被广泛使用，并且公司已经积累了大量由这类系统产生的信息。
数据挖掘这个概念广义上讲是指从大量数据中发现有关信息，或“发现知识”。与人工智能中的知识发现类似，数据挖掘试图自动从数据中发现统计规则和模式。但是，数
