智能管理决策门户体系结构研究

智能管理决策门户是一种将企业信息门户与商业智能技术集成在一起的新型解决方案。通过引入两级知识库、知识预生成、知识替换这三种机制，它能够满足用户对数据实时的、多样化的、动态的共享及交换的要求，而传统的商业智能技术则满足了将数据转化为期识．进而为企业服务的要求。     

浅谈BI系统在国泰公司的应用

BI(Business Intelligence)即商务智能,作为一种信息化技术用来将企业中现有的数据资源进行有效地整合和数据挖掘,实时地对ERP、CRM等管理工具生成的企业数据进行快速准确地分析并提出决策依据,帮助企业做出明智的业务经营决策。从而实现知识共享和知识创造紧密结合,完成数据资源从信息到知识的转变。本文结合实际着重分析了BI系统在国泰公司的应用,以及该系统对公司生产经营带来的转机,并阐述了商业智能的概念、体系结构和功能。     

智能管理决策门户体系结构研究

智能管理决策门户是一种将企业信息门户与商业智能技术集成在一起的新型解决方案。通过引入两级知识库、知识预生成、知识替换这三种机制,它能够满足用户对数据实时的、多样化的、动态的共享及交换的要求,而传统的商业智能技术则满足了将数据转化为知识,进而为企业服务的要求。     

BI在企业中的应用

商业智能(BI)作为正在快速发展的新兴技术,其主要运用人工智能技术分析和处理企业的数据,辅助企业做出快速反应,加快知识的获取速度以增加商业利润,满足管理层和决策层对信息知识时间性和准确性的要求。     

基于WCF的商业智能系统的应用研究

在信息化过程中,企业需要实时准确地寻找信息模型,不同企业之间知识信息和智能分析能力的共享和交互的需求变得越来越迫切.针对传统商业智能存在移植性、集成性和可扩展性差等弱点,文中研究基于WCF的商业智能平台.在分析商业智能当前应用状况和商业智能体系结构的基础上,给出了整个系统比较完善的解决方案.构建了基于WCF服务的商业智能的应用平台.该平台可以将商业智能组件无缝集成到企业现有的系统中,增强了可理解性和可扩展性.     

商业智能实战手册

从单独应用业务报表工具，到建立小型的数据集市、数据仓库，再到采用多维分析展示工具或者采用有助于知识发掘的数据挖掘工具——这些现象表明，商业智能已经逐渐步入企业不间层次的应用。那么，采用何种有效的应用模式才能保证商业智能项目的成功实施呢?     

商业智能在科技服务决策支持系统中的应用

在介绍了商业智能的核心技术和体系结构包括数据仓库、联机分析处理、数据挖掘等的基础上。通过分析科技信息服务这个特定领域的决策需求，给出了基于商业智能的科技服务决策支持系统的解决方案。实际应用表明该系统提高了科技信息供需双方对现有信息数据的利用效率，还提高了科技信息服务机构的决策分析能力。     

IBM雄霸软件市场

有数据显示,2000年IBM称雄商业智能(BI)市场,并在市场继续保持了盟主的地位。那么,IBM如何能独占商业智能市场鳌头呢?2001年IBM数据管理又将朝什么方向发展呢?日前,记者有机会采访到IBM软件部技术销售经理胡晓专先生。 胡先生介绍说,在电子商务时代,随着电子商务信息量的日益扩大,用户需要利用数据仓库、OLAP和数据挖掘等技术,从海量的历史数据中分     

机场数据仓库/商业智能平台的设计与实现

杭州萧山国际机场数字空港规划的落实,促使许多信息系统相继建成,在不少信息系统数据库中已经积累了大量的数据。建设机场的商业智能平台,实现数据的集成和共享,将积累的信息资源服务于管理决策势在必行。文章介绍了数据仓库和商业智能的相关概念,对机场数据仓库/商业智能平台的设计和构建作了阐述。目前该平台一期已经建成,并投入使用。     

商业智能三趋势

目前很多用户都在实施商业智能(B u s i n e s sIntelligence)项目,商业智能也是近年IT行业的关键投资领域之一,据统计,企业数据仓库和商业智能的市场已达到40亿美元,2008年该市场将达到100亿美元。那么,商业智能应用有哪些新的趋势?IBM商业智能软件亚太地区总经理尹丹岭认为,支持实时分析、对非结构化信息的集成、支持数据虚拟集中分析是商业智能的三大最新技术趋势。商业智能三维发展商业智能技术并不是基础技术或者产品技术,它是数据仓库、联机分析处理OLAP(Online AnalyticalProcessing)和数据挖掘等相关技术走向商业应用后形成的…     

联邦式异构数据库应用系统的集成框架和实现技术的研究

现代的企业业单位,由于种种原因,往往并存有多个基于数据库的异构应用系统,从而赞成企事业单位以共信息资源,为了解决企业事业面临的这一问题,从信息集成的角度出发,提出了一种基休成框架的数据集成新方法,并论述了数据映射,公共数据库接口及分布对象教育处等数据集成的关键技术。     

商业智能解决方案的研究与应用

信息技术在企业的广泛应用产生了大量的数据,这些数据中包含了对各级别的企业决策者极具价值的信息,但各个业务系统产生的分散、孤立的数据很少能被用于决策分析。要想有效地利用各种应用系统蕴藏的数据来提升企业决策水平,获得更大的竞争优势,实施企业商业智能战略是至关重要的。通过商业智能关键技术的研究给出了一个商业智能较为完整的解决方案,并结合项目实践,重点研究了商业智能在航运企业中的应用。最后给出了某航运企业商业智能系统的应用实例。商业智能关键技术若推广于军用舰艇管理,则具有重大的国防意义。     

Is business intelligence a smart move?

As businesses continue to use computer systems for a growing number of functions, they face the challenge of processing and analyzing huge amounts of data and turning it into profits. In response to this, vendors are trying to upgrade their business intelligence (BI) products, which are sets of tools and technologies designed to efficiently extract useful information from oceans of data. If successful, upgrading the technology would not only help users but could also let BI vendors widen their products' audience. However, despite the recent improvements, widespread adoption still faces several key challenges, such as high costs and the need for BI systems to integrate and interoperate with the many heterogeneous corporate data sources. The paper discusses new BI trends and considers Web-based BI. It reviews the obstacles to BI adoption     

A model of customer relationship management and business intelligence systems for catalogue and online retailers

As more retailers evolve into customer-centric and segment-based business, business intelligence (BI) and customer relationship management (CRM) systems are playing a key role in achieving and maintaining competitive advantage. For the past ten years, the authors have had the rare opportunity of observing and interviewing employees and managers of three different management teams at three separate Fingerhut companies as they experimented with various ITs for their companies. When the first Fingerhut company peaked in 1998, as many as 200 analysts and 40 statisticians mined the database for insights that helped predict consumer shopping patterns and credit behaviour. Data mining and BI helped Fingerhut spot shopping patterns, bring product offerings to the right customers, and nurture customer relationships. By 1998, Fingerhut was the second largest catalogue retailer in the U.S. with revenues nearing $2 billion. However, after Federated acquired Fingerhut in 1999 and made it a subsidiary, Fingerhut Net, it suffered great losses and was eventually liquidated. Finally, a new company, Fingerhut Direct Marketing, was resurrected in 2002 under a new management team, and it once again became successful. What went right? What went wrong? The paper concludes with CRM and BI systems success factors and a discussion of lessons learned.     

Business intelligence in enterprise computing environment

Business intelligence (BI) is the process of gathering correct information in the correct format at the correct time; and delivering the results for decision-making purposes, or have a positive impact on business operations, tactics, and strategy in the enterprises. This paper is intended as a brief review of BI in an enterprise computing environment, with an emphasis on the algorithms and methods. The review points out the challenges to the broad and deep deployment of business intelligence systems, and provide proposals to make business intelligence more effective.     

A novel approach to conduct the importance-satisfaction analysis for acquiring typical user groups in business-intelligence systems

Business intelligence (BI) is a powerful tool to conduct causality analysis and corporate diagnoses since it provides a data-driven approach to link firms' strategic goals into tactical policies and operational actions. Specifically, BI consists of a series of architectures and techniques like database, data warehousing, and data mining that transform raw data into useful information to provide decision supports. In reality, typical BI user groups involve financial analysts, marketing planners, general managers, field staffs, upstream suppliers, and downstream customers. Inspired by the concept of STP (segmentation-target-positioning) and product family design, BI systems need to be customized to satisfy diverse user groups and tailored to a firm for solving complicated but specific business problems. Consequently, a novel framework is proposed to fulfill the following goals: (1) incorporating user preferences to identify key design features that best fit BI's main segments for achieving customer acquisition, (2) transforming user perceptions into quantitative degrees of satisfaction for accomplishing customer retention, and (3) conducting the importance-satisfaction analysis to generate managerial insights for developing next-generation BI systems.     

Towards an understanding of the role of business intelligence systems in organisational knowing

Recent advances in information technology (IT), such as the advent of business intelligence (BI) systems, have increased the ability of organisations to collect and analyse data to support decisions. There is little focus to date, however, on how BI systems might play a role in organisational knowledge creation – in organisational knowing. We develop a conceptual framework of organisational knowing based on a synthesis of the literature, and use this as a framework to investigate how BI systems facilitate knowing in a case organisation. We identify two practices triggered by BI systems that distinguish them from prior applications of IT: the ability to initiate problem articulation and dialogue, and that of data selection (e.g. to address information needs of organisational decision makers at different managerial levels). This study provides empirical evidence of the performative outcome of BI systems in relation to organisational knowing through the practices of articulation and data selection. It provides a practice perspective on BI and focuses on the role of BI systems in organisational knowing thereby opening up a new departure for BI research that considers the implications of BI systems in organisations with actual practice in mind.     

数据仓库中数据质量控制研究

随着数据仓库的深入应用,数据质量问题成为关系到数据仓库建设成败和数据能否有效应用的重要关键问题。该文首先讨论数据仓库环境下存在的数据质量问题以及保证数据质量的重要性,然后提出数据质量的度量和评价指标,最后给出了数据仓库实施和运行过程中数据质量控制的数据质量成熟度模型和保证仓库数据质量的方法。     

基于Pentaho的商业智能系统

目前多数企业在构建自己的商业智能解决方案时还是寻求专业厂商的支持.这里把目光转向开源项目,提出在企业中利用Pentaho平台,构建商业智能系统这个新思路.阐述了构建基于Pentaho的商业智能系统的一些关键技术要点,内容包括流程设计,OLAP设计,ETL设计和分析界面设计等方面,同时指出了该平台的广阔应用前景.     

数据仓库应用系统技术研究

对数据仓库应用系统的一般解决方案以及六大技术结合目前市场上流行的三大数据仓库解决方案及其产品进行了系统地分析 ,以期对企业在建设数据仓库应用系统的过程中有所借鉴和帮助。