The Data Warehouse Model Based on Web Service Technology

This paper analyses the advantages of comhining Web service and data warehouse, then introduces a distributed data warehouse model based on Web service. It also introduces some features of Web services and data warehouse, Web service is a bridge, which can link different models, different operation systems and different program languages. With the development and application of Web service technology, the current operation of design and application will shift to develop and make use of Web service. Web service will matke ＂software as service＂ come true and finally let people think software is of great value, and its value can be embodied and transferred on the web. As a decision supporting system, data warehouse provides a solid plattbrm formed by current data and past data. Using this platform, companies can make a series of commerce analysis. This work combines the Web service and data warehouse, extends data warehouse＇s network ability. Then, Companies Corporation and individual can obtain information conveniently.     

采用移动代理技术建立数据仓库的研究

The thesis sets forth for the policy maker a way of achieving the aim of building model data warehouse based on relation model distributed database by using Mobile Agent technology. According to the design principal of data warehouse and the standard technology,author puts forward forming metadatas by tree pattern or forests strctur-e,giving the definition of metadata. Model and the general principal of combining metadatas to form data warehouse and showing a picture tool of data warehouse designing system. It creates a Mobile Agent orieinal form that can realize the constrction of data warehouse based on relation model distributed database.     

Application of data warehouse in power transformer diagnosis system

Electric power companies have accumulated huge amounts of historical fault data of power transformer after many years operation, but the decision-makers have not been greatly supported because of the limitation of knowledge and can not make decision for transformer condition assessment. A real power corporation is selected as the research background. Based on analyzing and reorganizing the various existing data sources, the power transformer fault information data warehouse is constructed and snowflake mode cubes for multi-dimension data are established. By using Processing） and data mining analyzing and inquiring data OLAP（On-Line Analysis technology, forecasting load, warehouse are realized from different point view and multi-layers, including rolling up, drilling down, slicing, dicing and rotating etc.. Moreover, this paper proposes a novel transformer fault data mining system based on data warehouse. Finally, bayes network of fault patterns are obtained, which can greatly help the decision-making for the system operating and management. The results show that transformer fault diagnosing system based on data warehouse technology can provide efficient decision supporting.     

A New ETL Approach Based on Data Virtualization

ETL (Extract-Transform-Load) usually includes three phases: extraction, transformation, and loading. In building data warehouse, it plays the role of data injection and is the most time-consuming activ...     

数据仓库的质量管理问题和方法

A data warehouse is often a large-scale information system for an enterprise,so its quality management isimportant and difficult. Recently, some researchers have studied the problems of quality management in data ware-houses from different views ,and achieved some good results. This paper will broadly introduce the concept ,methods and techniques in quality management in data warehouses ,and discuss the important quality factors in data warehous-es in detail.     

数据仓库和数据挖掘

Making a business decision using data from severaldifferent enterprise databases can be complicated. Data warehousesconsolidate data into a central repository and give you the OLAP toolsnecessary to retrieve data pertinent to the solution.DefinitionA data warehouse is used to consolidate this data into a central storeand to arrange it to make analysis easier, which means the data is lessnormalized than your traditional application database. Data is typicallytransferred in batch to the centra…     

Compressed Data Cube for Approximate OLAP Query Processing

Approximate query processing has emerged as an approach to dealing with the huge data volume and complex queries in the environment of data warehouse.In this paper,we present a novel method that provides approximate answers to OLAP queries.Our method is based on building a compressed (approximate) data cube by a clustering technique and using this compressed data cube to provide answers to queries directly,so it improves the performance of the queries.We also provide the algorithm of the OLAP queries and the confidence intervals of query results.An extensive experimental study with the OLAP council benchmark shows the effectiveness and scalability of our cluster-based approach compared to sampling.     

Prefix Code Translation by Mapping

This paper introduces a new way of prefix code translation.It helps to finish the whole translation by mapping once (only one comparison instruction is needed for getting the length of prefix code),and returns the original data and the length of prefix code element.The decoding time is only about four times as many as the time accessing original data directly.     

L-Tree Match: A New Data Extraction Model and Algorithm for Huge Text Stream with Noises

In this paper, a new method, named as L-tree match, is presented for extracting data from complex data sources. Firstly, based on data extraction logic presented in this work, a new data extraction model is constructed in which model components are structurally correlated via a generalized template. Secondly, a database-populating mechanism is built, along with some object-manipulating operations needed for flexible database design, to support data extraction from huge text stream. Thirdly, top-down and bottom-up strategies are combined to design a new extraction algorithm that can extract data from data sources with optional, unordered, nested, and/or noisy components. Lastly, this method is applied to extract accurate data from biological documents amounting to 100GB for the first online integrated biological data warehouse of China.     

A novel feature selection framework for automatic web page classification

The number of Internet users and the number of web pages being added to WWW increase dramatically every day.It is therefore required to automatically and e?ciently classify web pages into web directories.This helps the search engines to provide users with relevant and quick retrieval results.As web pages are represented by thousands of features,feature selection helps the web page classifiers to resolve this large scale dimensionality problem.This paper proposes a new feature selection method using Ward s minimum variance measure.This measure is first used to identify clusters of redundant features in a web page.In each cluster,the best representative features are retained and the others are eliminated.Removing such redundant features helps in minimizing the resource utilization during classification.The proposed method of feature selection is compared with other common feature selection methods.Experiments done on a benchmark data set,namely WebKB show that the proposed method performs better than most of the other feature selection methods in terms of reducing the number of features and the classifier modeling time.     

基于银行数据仓库的元数据管理系统

元数据在银行数据仓库中具有重要意义。讨论元数据的分类和作用,分析元数据的管理功能,给出一种基于银行数据仓库的元数据管理系统,对其结构进行分析和说明。实践结果表明,该系统可以加强对数据的分析和管理能力,提高银行数据仓库等决策系统的灵活性和可扩展性。     

室内人体运动目标的自动跟踪方法

元数据在银行数据仓库中具有重要意义.讨论元数据的分类和作用,分析元数据的管理功能,给出一种基于银行数据仓库的元数据管理系统,对其结构进行分析和说明.实践结果表明,该系统可以加强对数据的分析和管理能力,提高银行数据仓库等决策系统的灵活性和可扩展性.     

数据仓库元数据管理研究与架构设计

数据仓库是信息化发展到一定程度的产物,能够为决策支持提供强有力的支持。在构建数据仓库的过程中,需要集成众多不同的软件系统,以及设计许多模型。元数据在数据仓库的设计、集成、实现中扮演重要角色。文章结合CWM标准,对数据仓库元数据的管理架构,元数据管理系统结构,元数据存储方法等进行了研究。     

基于元数据的数据仓库安全模型实现研究

元数据是数据仓库的关键技术之一,也是数据仓库安全性的解决途径之一。对基于元数据的数据仓库安全模型进行了研究,对原模型进行了改进,并提出了在Oracle9i数据仓库平台上的解决方案。     

数据仓库中元数据标准的研究

元数据是数据仓库项目取得成功的关键因素之一，而元数据标准又是成功管理元数据的关键。文中介绍了数据仓库中元数据的意义，以及MDC的开放信息模型OIM和OMG的元数据规范MOF，并结合实际总结了其它几种元数据标准，在此基础上指出了元数据标准的发展方向。     

数据仓库中元数据技术研究

元数据及其管理是数据仓库系统的核心部件,是内部技术人员开发与维护数据仓库的蓝图,是商业终端用户导航数据仓库以及定位有用信息的路标。该文详细介绍了无数据的功能及其管理,然后简单介绍了元数据联盟的开放信息模型。     

应用元数据开发数据映射辅助工具

数据映射在数据仓库项目中扮演十分重要的角色,它是ETL开发的前提条件,也是ETL开发过程中详细设计的一部分。本文在中国太平洋保险公司（CPIC）建设企业数据仓库（EDW）的项目背景下对企业数据仓库中的元数据应用作了研究,记述一个简单的元数据驱动的数据映射工具的开发过程,以说明元数据对数据集成工具开发的重要性。     

应用元数据开发数据映射辅助工具

数据映射在数据仓库项目中扮演十分重要的角色,它是ETL开发的前提条件,也是ETL开发过程中详细设计的一部分。本文在中国太平洋保险公司(CPIC)建设企业数据仓库(EDW)的项目背景下对企业数据仓库中的元数据应用作了研究,记述一个简单的元数据驱动的数据映射工具的开发过程,以说明元数据对数据集成工具开发的重要性。     

基于模型驱动元数据集成体系结构研究与设计

元数据及其管理是数据仓库和业务分析领域中的核心部分,也是成功建立信息供应链的关键。元数据管理依赖于软件体系结构来抽取、集成、存储和发布元数据。这样的体系结构通常以元数据存储库为核心。提出了一个基于CWM(CommonWarehouseMetamodel)元模型的元数据集成体系结构,并对体系结构中的相关组件和技术进行了简要介绍。     

Development of a clinical data warehouse from an intensive care clinical information system

There are relatively few institutions that have developed clinical data warehouses, containing patient data from the point of care. Because of the various care practices, data types and definitions, and the perceived incompleteness of clinical information systems, the development of a clinical data warehouse is a challenge.In order to deal with managerial and clinical information needs, as well as educational and research aims that are important in the setting of a university hospital, Erasmus Medical Center Rotterdam, The Netherlands, developed a data warehouse incrementally. In this paper we report on the in-house development of an integral part of the data warehouse specifically for the intensive care units (ICU-DWH). It was modeled using Atos Origin Metadata Frame method. The paper describes the methodology, the development process and the content of the ICU-DWH, and discusses the need for (clinical) data warehouses in intensive care.