英语翻译2.What is Data MiningGenerally,data mining (sometimes ca
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英语翻译
2.What is Data Mining
Generally,data mining (sometimes called data or
knowledge discovery) is the process of analyzing data
from different perspectives and summarizing it into
useful information - information that can be used to
increase revenue,cuts costs,or both.Data mining
software is one of a number of analytical tools for
analyzing data.It allows users to analyze data from
many different dimensions or angles,categorize it,and
summarize the relationships identified.Technically,
data mining is the process of finding correlations or
patterns among dozens of fields in large relational
databases [5][6] .
Data are any facts,numbers,or text that can be
processed by a computer.Today,organizations are
accumulating vast and growing amounts of data in
different formats and different databases.This includes:
(1) Operational or transactional data such as,sales,
cost,inventory,payroll,and accounting
(2) No operational data,such as industry sales,forecast
data,and macro economic data
(3) Meta data - data about the data itself,such as
logical database design or data dictionary definitions
The patterns,associations,or relationships among
all this data can provide information.For example,
analysis of retail point of sale transaction data can
yield information on which products are selling and
when.
Information can be converted into knowledge
about historical patterns and future trends.For example,
summary information on retail supermarket sales can
be analyzed in light of promotional efforts to provide
knowledge of consumer buying behavior.Thus,a
manufacturer or retailer could determine which items
are most susceptible to promotional efforts.
Dramatic advances in data capture,processing
power,data transmission,and storage capabilities are
enabling organizations to integrate their various
databases into data warehouses.Data warehousing is
defined as a process of centralized data management
and retrieval.Data warehousing,like data mining,is a
relatively new term although the concept itself has
been around for years.Data warehousing represents an
ideal vision of maintaining a central repository of all
organizational data.Centralization of data is needed to
maximize user access and analysis.Dramatic
technological advances are making this vision a reality
for many companies.And,equally dramatic advances
in data analysis software are allowing users to access
this data freely.The data analysis software is what
supports data mining.
2.What is Data Mining
Generally,data mining (sometimes called data or
knowledge discovery) is the process of analyzing data
from different perspectives and summarizing it into
useful information - information that can be used to
increase revenue,cuts costs,or both.Data mining
software is one of a number of analytical tools for
analyzing data.It allows users to analyze data from
many different dimensions or angles,categorize it,and
summarize the relationships identified.Technically,
data mining is the process of finding correlations or
patterns among dozens of fields in large relational
databases [5][6] .
Data are any facts,numbers,or text that can be
processed by a computer.Today,organizations are
accumulating vast and growing amounts of data in
different formats and different databases.This includes:
(1) Operational or transactional data such as,sales,
cost,inventory,payroll,and accounting
(2) No operational data,such as industry sales,forecast
data,and macro economic data
(3) Meta data - data about the data itself,such as
logical database design or data dictionary definitions
The patterns,associations,or relationships among
all this data can provide information.For example,
analysis of retail point of sale transaction data can
yield information on which products are selling and
when.
Information can be converted into knowledge
about historical patterns and future trends.For example,
summary information on retail supermarket sales can
be analyzed in light of promotional efforts to provide
knowledge of consumer buying behavior.Thus,a
manufacturer or retailer could determine which items
are most susceptible to promotional efforts.
Dramatic advances in data capture,processing
power,data transmission,and storage capabilities are
enabling organizations to integrate their various
databases into data warehouses.Data warehousing is
defined as a process of centralized data management
and retrieval.Data warehousing,like data mining,is a
relatively new term although the concept itself has
been around for years.Data warehousing represents an
ideal vision of maintaining a central repository of all
organizational data.Centralization of data is needed to
maximize user access and analysis.Dramatic
technological advances are making this vision a reality
for many companies.And,equally dramatic advances
in data analysis software are allowing users to access
this data freely.The data analysis software is what
supports data mining.
2.什么是数据采矿
通常,数据采矿 (有时呼叫数据或
知识发现) 是分析数据的程序
从不同的远景而且概述它进入
有用的数据 - 能习惯于的数据
增加收入,削减花费,或两者的.数据采矿
软件是一些分析的工具之一
分析数据.它让使用者分析数据从
许多不同的尺寸或角度,分类它,和
概述被识别的关系.技术上,
数据采矿是发现相互关系的程序或
在几十个领域之中的式样大致上表示关系的
数据库 [5][6].
数据是任何的能是的事实、数字或本文
根据一部计算机处理.今天,组织是
累积巨大的而且增加数据的数量进入
不同的格式和不同的数据库.这包括:
(1) 操作或交易的数据如此的当做,售卖,
费用,详细目录,薪资帐册和会计
(2) 没有操作的数据,像是工业售卖,预测
数据、和句集经济的数据
(3) 关于数据本身的 Meta 数据 - 数据,像是
合乎逻辑的数据库设计或数据字典定义
式样、协会或关系在
所有的这数据能提供数据.举例来说,
售卖交易数据罐子的零售点的分析
产生产品正在卖的关于的资讯和
当.
数据能转换成知识
有关历史的式样和将来的趋势.举例来说,
关于零售的摘要资讯自选市场售卖罐子
被分析因为增进的努力提供
买行为的消费者的知识.因此,一
制造业者或零售商可以决定哪一个计算
大多数的易受影响者是对增进的努力.
在数据抓取中的戏剧性的进步,处理
力量,数据传输、和储藏能力是
促成组织整合他们的各种不同的
进入数据仓库之内的数据库.储入仓库的数据是
定义当做一个集中数据的程序管理
而且取回.数据储入仓库,像数据采矿,是一
相对新的期限虽然观念本身有
是在长达数年之久周围.储入仓库的数据表现一
维持中央容器的理想视觉所有的
组织的数据.数据的集中是不可或缺的到
取使用者通路和分析最大值.戏剧性的
科技的进步正在使这视觉成为真实
对于许多公司.并且,相等戏剧性的进步
在数据分析软件中让使用者存取
自由地的这一笔数据.数据分析软件是什么
支持数据采矿.
通常,数据采矿 (有时呼叫数据或
知识发现) 是分析数据的程序
从不同的远景而且概述它进入
有用的数据 - 能习惯于的数据
增加收入,削减花费,或两者的.数据采矿
软件是一些分析的工具之一
分析数据.它让使用者分析数据从
许多不同的尺寸或角度,分类它,和
概述被识别的关系.技术上,
数据采矿是发现相互关系的程序或
在几十个领域之中的式样大致上表示关系的
数据库 [5][6].
数据是任何的能是的事实、数字或本文
根据一部计算机处理.今天,组织是
累积巨大的而且增加数据的数量进入
不同的格式和不同的数据库.这包括:
(1) 操作或交易的数据如此的当做,售卖,
费用,详细目录,薪资帐册和会计
(2) 没有操作的数据,像是工业售卖,预测
数据、和句集经济的数据
(3) 关于数据本身的 Meta 数据 - 数据,像是
合乎逻辑的数据库设计或数据字典定义
式样、协会或关系在
所有的这数据能提供数据.举例来说,
售卖交易数据罐子的零售点的分析
产生产品正在卖的关于的资讯和
当.
数据能转换成知识
有关历史的式样和将来的趋势.举例来说,
关于零售的摘要资讯自选市场售卖罐子
被分析因为增进的努力提供
买行为的消费者的知识.因此,一
制造业者或零售商可以决定哪一个计算
大多数的易受影响者是对增进的努力.
在数据抓取中的戏剧性的进步,处理
力量,数据传输、和储藏能力是
促成组织整合他们的各种不同的
进入数据仓库之内的数据库.储入仓库的数据是
定义当做一个集中数据的程序管理
而且取回.数据储入仓库,像数据采矿,是一
相对新的期限虽然观念本身有
是在长达数年之久周围.储入仓库的数据表现一
维持中央容器的理想视觉所有的
组织的数据.数据的集中是不可或缺的到
取使用者通路和分析最大值.戏剧性的
科技的进步正在使这视觉成为真实
对于许多公司.并且,相等戏剧性的进步
在数据分析软件中让使用者存取
自由地的这一笔数据.数据分析软件是什么
支持数据采矿.
英语翻译2.What is Data MiningGenerally,data mining (sometimes ca
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