摘要
BI(Business Intelligence)应用已成为现代企业信息化建设达到一定阶段后的必然选择,其主要任务是完成对数据的收集清理整合、分析挖掘模型构建和分析展现,使企业各级决策者便捷获取决策知识,辅助提高问题洞察力,从而快速有效做出对企业有利的决策。传统商业智能技术体系从理论上看已经比较完备,但在实际应用过程中由于存在数据模型快速有效构建和数据准确性保障等方面关键技术瓶颈,使得应用效果受限,用户投入产出性价比不佳。文章针对这些瓶颈问题,结合行业需求,经过长期产品研发与实施服务实践,力求探索一条解决之道,并已取得初步成效。
Business Intelligence （BI） application has become the inevitable choice when the information construction of modern enterprises comes to a certain stage. The main task of BI is to accomplish data collection, sorting, integration, analysis, mining, model building and demonstration. All-level enterprise decision makers can easily obtain the decision-making knowledge, and with sharp insights into the problems they can make quick and effective decisions that benefit the enterprise. The traditional BI technical system is comparatively mature theoretically, but has several key technical bottlenecks in the real application process, such as quick and effective constlaiction of data models, data accuracy guarantee, and etc. These bottlenecks limit the application effects and lower the customer input-output ratio. This paper attempts to explore a solution to these bottleneck problems according to the industry requirements and the long-time product development and implementation practice experience.
出处
《电力信息化》
2011年第7期50-53,共4页
Electric Power Information Technology
关键词
商业智能
数据挖掘
数据分析
决策支持
Business Intelligence
data mining
data analysis
decision-making support
