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Closing the Gap between Data Mining and Business Users of Business Intelligence Systems: A Design Science Approach

机译:缩小数据挖掘与商业智能系统业务用户之间的鸿沟:一种设计科学方法

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摘要

Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.
机译:自从1958年Lunh首次使用商务智能(BI)一词以来,信息系统和技术领域就发生了重大变化,特别是在决策支持系统领域。 BI系统已在组织中广泛使用,其重要性已得到认可。这些系统作为完整的业务知识的不可或缺的部分,是支持决策的不可替代工具。数据挖掘(DM)工具在BI领域的传播日趋广泛,并认识到其在企业BI系统中的使用意义。 BI工具是友好的,迭代的和交互式的,使业务用户可以轻松访问。用户可以直接操纵数据,并具有提取包含在该业务数据中的所有价值的能力。在BI领域中使用DM指出的问题与以下事实有关:DM模型很复杂,以便由业务用户直接操纵,而不包括BI工具。 BI工具的不存在使业务用户可以直接操纵DM模型,这被认为是问题所在。本文介绍了更多这些问题,可能的解决方案和结论。

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