东莞理工学院城市学院-高考排名查询

附录1 外文原文
Data warehouse technique
The data warehouse says all
The data warehouse is an environment, not a product. It provides the decision that
customer used for current history data supports, these data is very difficult in
traditional operation type database or can't get, say more tangibly, the data warehouse
is a kind of system construction. Data warehouse than it customer relation the
management is a concept that is been familiar with by person, it is 1991 the United
States an information engineering learns what house W.H. Inmon Doctor put
forward, its definition is
the topic of, gather of, at any time but change of, the last long data gathers
The technique system construction of the data warehouse
The data of obtains mold piece: Used for obtaining the data from the source
document with the source database, combine the proceeding sweep, delivering,
adding it to data warehouse database inside.
· Data management mold piece: Used for the movement of the management data
warehouse.
· Delivers mold piece: Used for the other warehouse in direction with assign the data
warehouse data in the exterior system.
· The data is in the center a mold piece: The end customer in direction tool that used
for the method provides the interview data warehouse database.
· Data interview mold piece: Used for providing the interview for the end customer of
the business enterprise with the tool of the analysis data warehouse data.
· Design mold piece: Used for the design data warehouse database.
· Information catalogue mold piece: Used for governor to provide with the customer
relevant saving contents in data warehouse data in the database with meaning
information.
How to establish the data warehouse
Current, the internal calculator in business enterprise system is mutually
independent, the data rule( legitimacy) demand of the system that have is affirmed
from the other system, various data lacks to gather sex, conduct and actions trend, the
data warehouse technique is an one of the most emollient way to makes these data
gathered get ups, the data warehouse establishes can at logical realize various system
interaction operation, this lay the foundation for the modern college in developments,
also leads for the college layer science decision offering guarantees powerfully. The

process that establish in the data warehouse needs below step:
1. Establish the data model to the end business need. The design of the data model
not only consider only to the first topic, but also looks after both sides the need of the
other management in college decision topic to searches the need of the topic with
every kind of data, statement.
2. The certain topic proceeding data sets up the mold. According to the decision
need certain topic, choice data source, proceed logic construction design.
3. The database of the design data warehouse. Put great emphasis on the saving
construction in physics that apply in the topic development data warehouse inside
data.
4. Definition data source. According to the topic data model, choose different
operation type database as the data source.
5. Establish the model for a data. The model made sure into the data scope of the
data warehouse, and with provision of relevant data. Complete a data, can let
customer known, the data warehouse inside has actually what data, the data gathers
the level of structure with how detailed degree is, can provide what information, how
these information are carried calculates with organizes etc..
6. Take( Extract), convert( Transmit), add from the operation type database inside
take out the data that carry( Load) the database inside arrive the data warehouse.
7. Choice data interview analysis tool, the customer will use the saving information
within these toolses interview data warehouse, realizing decision support need.
The data scoops out the technique
Along with the database technical develop continuously and extensive application
in each profession in system in management in database, the backlog enlarges in the
nasty play in amount of data in the database, but among them can use directly
however opposite less in amount of information.
People have been hoping can to conceal in the superficial information in these
data, proceed many level of structures analyze, for the purpose of better land
utilization acquire the benefit to operate in the business with these data, increase the
information of the social competition ability.
Current every kind of database management system although can realizes
efficiently the data record into and search, statistics to wait the function, can't discover
relation existed in the data with regulation, resulted in like this and then a kind of
data Bang and knowledge needy keep both of phenomenon. According to the
inquisition, the data collections increase with saving with every year 130% speed, but
in the data only have 2% data to is analyzed availably. This exploitation that scoop
out provided the vast space for the data .To the 2004, apply to attain USD
1,000,000,000 in the data of the electronic commerce market of scooping out the tool.

附录2 外文资料译文
数据仓库技术
数据仓库概述
数据仓库是一个环境，而不是一件产品。它提供用户用 于决策支持的当前历
史数据，这些数据在传统的操作型数据库中很难或不能得到，更确切地说，数据仓库是一种体系结构。数据仓库较之客户关系管理是一个被人熟知的概念，它是
1991年美国著名 信息工程学家博士提出的，将其定义为 “数据仓库
是支持决策过程的面向主题的、集成的、随时间而改变的、持久的数据集合”。
数据仓库的技术体系结构
·数据获取模块：用于从源文件和源数据库中获取数据，并进行清洁 ,传输，
将它加到数据仓库数据库中。
·数据管理模块：用于管理数据仓库的运行。
·数据传递模块：用于向其他仓库和外部系统中分配数据仓库数据。
·中间件模块：用于向最终用户工具提供访问数据仓库数据库的方法。
·数据访问模块：用于为企业的最终用户提供访问和分析数据仓库数据的工
具。
·设计模块：用于设计数据仓库数据库。
·信息目录模块：用于为管理者和用户提供有关存储 在数据仓库数据库中的
数据的内容和含义信息。
如何建立数据仓库
目前，企业内部 的计算机系统相互独立，有的系统的数据规则性（合法性）
需要从其它系统中得到认定，各类数据缺乏集 成性，作为趋势，数据仓库技术是
使这些数据集成起来的最有力的方式之一，数据仓库的建立能在逻辑上 实现各类
系统互动操作，这就为建设现代化学院奠定基础，也为学院领导层科学决策提供
强有力 的保证。建立数据仓库的过程中需要以下步骤：
1．对最终业务需求建立数据模型。数据模型的设计不 仅仅考虑对最初主题，
还要兼顾学院其他管理决策主题的需求和各种数据、报表查询主题的需求。
2．确定主题进行数据建模。根据决策需求确定主题，选择数据源，进行逻
辑结构设计。
3．设计数据仓库之数据库。着重于应用于主题开发数据仓库中数据的物理
存储结构。
4．定义数据源。根据主题数据模型，选择不同的操作型数据库为数据源。
5．为元数据建立 模型。模型确定了进入数据仓库的数据范围，以及与数据
有关的规定。完备的元数据，能让用户知道，数 据仓库中究竟有什么数据，数据
汇总层次和详细程度如何，能提供什么信息，这些信息是如何运算和组织 等。
6．从操作型数据库中抽取（Extract）、转换（Transmit）、加载（Load） 数
据到数据仓库之数据库中。
7．选择数据访问分析工具，用户将使用这些工具访问数据仓库 中的存储信

息，实现决策支持需求
[11]
。
数据挖掘技术
随着数据库技术的不断发展及数据库管理系统在各个行业的广泛应用，积累
在数据库中的数据量 急剧增大，但其中可直接使用的信息量却相对较少。人们一
直希望能够对隐藏在这些数据表面的信息，进 行多层次分析，以便更好地利用这
些数据获得利于商业运作，提高社会竞争力的信息。目前的各种数据库 管理系统
虽可以高效地实现数据的录入、查询、统计等功能，但无法发现数据中存在的关
系和规 律，这样便造成了一种数据爆炸与知识贫乏并存的现象。据调查，数据收
集与存储以每年130%的速度 增长，但数据中只有2%的数据被有效地分析。这为
数据挖掘的利用提供了广阔的空间。到2004年， 应用于电子商务的数据挖掘工
具的市场达到10亿美元。