数据仓库与数据挖掘技术在商业智能中的设计与应用

摘    要

在当今信息化时代，商业智能已逐渐成为企业获取竞争优势、提升决策效能的关键所在。其中，数据仓库与数据挖掘技术作为商业智能的重要支撑，其设计与应用对于企业的数据整合、信息提取和智能分析具有不可或缺的作用。本文旨在探讨数据仓库与数据挖掘技术在商业智能中的设计与应用，以期为企业构建高效、智能的商业智能系统提供有益的参考。在数据仓库的设计方面，重点在于构建一个能够整合多源数据、支持复杂查询和分析的集中式数据存储环境。通过抽取、转换、加载等过程，将分散在企业各个业务系统中的数据进行整合和清洗，形成统一的数据视图，为后续的数据挖掘和智能分析提供坚实的基础。同时，数据仓库还需要考虑数据的存储结构、索引策略以及查询优化等方面，以确保数据的查询和分析性能。数据挖掘技术则是商业智能中的核心分析手段，它能够从海量数据中提取出有价值的信息和模式，为企业的决策提供有力支持。数据挖掘技术包括分类、聚类、关联规则挖掘、时间序列分析等多种方法，可以根据企业的具体需求选择适合的算法进行应用。通过数据挖掘，企业可以发现潜在的市场趋势、客户行为规律以及业务运营中的优化点，从而提升业务效率和盈利能力。在商业智能的应用中，数据仓库与数据挖掘技术相互协作，共同实现对企业数据的深度挖掘和智能分析。


关键词：数据仓库  数据挖掘  商业智能  


Abstract 
In today's information age, business intelligence has gradually become the key for enterprises to obtain competitive advantages and improve decision-making efficiency. Among them, data warehouse and data mining technology is an important support of business intelligence, and its design and application play an indispensable role in data integration, information extraction and intelligent analysis of enterprises. This paper aims to discuss the design and application of data warehouse and data mining technology in business intelligence, in order to provide useful reference for enterprises to build efficient and intelligent business intelligence system. In the design of data warehouse, the focus is on building a centralized data storage environment that can integrate multi-source data and support complex queries and analysis. Through the extraction, conversion, loading and other processes, the data scattered in each business system of the enterprise is integrated and cleaned to form a unified data view, which provides a solid foundation for subsequent data mining and intelligent analysis. At the same time, the data warehouse also needs to consider the data storage structure, index strategy and query optimization to ensure the data query and analysis performance. Data mining technology is the core analysis means of business intelligence, which can extract valuable information and patterns from massive data and provide strong support for enterprise decision-making. Data mining technology includes classification, clustering, association rule mining, time series analysis and other methods, which can be applied according to the specific needs of enterprises. Through data mining, enterprises can discover potential market trends, customer behavior rules and optimization points in business operations, thereby improving business efficiency and profitability. In the application of business intelligence, data warehouse and data mining technology cooperate with each other to realize the deep mining and intelligent analysis of enterprise data.


Keyword:Data warehouse  Data mining  Business intelligence 




目    录
1引言 1
2数据仓库与数据挖掘技术概述 1
2.1数据仓库技术概述 1
2.2商业智能概念 1
2.3相关技术集成 2
3商业智能系统设计 2
3.1系统需求分析 2
3.2数据仓库设计 3
3.3数据挖掘模块设计 4
3.4用户界面设计 4
4数据仓库与数据挖掘技术的实现 5
4.1数据仓库构建 5
4.2数据挖掘实施 6
4.3系统集成测试 6
4.4系统部署与应用 7
5结论 8
参考文献 9
致谢 10