Competitive pressures and a thriving new economy have driven thousands of businesses around the world to make enormous investmen

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问题    Competitive pressures and a thriving new economy have driven thousands of businesses around the world to make enormous investments in their information technology solutions. Investments in enterprise resource planning (ERP) software and customer relationship management (CRM) solutions arc only two examples of the new trends. Businesses use ERP software to improve operational efficiency and increase profitability, and CRM solutions to automate customer interaction processes that improve customer service and increase sales productivity.
    hi today’s modem technological world, companies are data rich and information poor. The growing need to anticipate changing market conditions and customer preferences, develop intelligent business plans, and act proactively is fueled by the availability of critical information. And because so much of that essential information is locked away within ERP, CRM and other transaction-oriented systems, the need for data warehousing is more compelling than ever.  Without the ability to move from data to information to knowledge to action, companies cannot stay competitive in today’s modem and ever changing economy.
    Early data warehousing efforts focused on separating the decision-support environment from operational transaction-processing systems. The ultimate goal was to create a centralized source of data for accurate, consistent reporting. The greatest cost of implementing data warehouses comes from the process of extracting, transforming and integrating data from source systems.

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答案 竞争压力以及新经济的繁荣迫使世界上数以千计的企业在信息技术方法方面投入大量资金。在企业资源管理软件和客户关系管理方法上的投资仅是这种新趋势的两个例子。企业运用企业资源管理软件来提高经营效率和增加利润;运用客户关系管理方法使客户作用过程自动化,以此来提高客户服务质量并增加销售量。 在当前的现代科技世界里,企业往往是数据充裕而信息贫乏。预期市场环境及消费者偏好的变化、制订明智的企业计划、敏捷地做出反应,这些不断增长的需要无异于依赖关键信息的有效性。而且由于大量的基本信息都存储在企业资源计划、客户关系管理或其他一些业务导向的系统里,因而数据库的建立愈发显得有必要了。缺乏从数据到信息,从信息到知识,从知识到行动的能力,企业将很难在当今现代化、变化多端的经济环境里保持竞争地位。 早期的数据库旨在把决策支持环境从操作型业务过程系统中分离出来。最终的目的是为准确、连续的报告建立一个中心数据源。实施数据库的最大成本来自于从源系统中提取,转化,并融合数据的过程。

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