本文以数据仓库为基础，与目前流行的联机分析处理、数据挖掘等技术相结合，提出了基于此的决策支持系统的设计。
Take data warehouse as foundation, with the aid of on Line Analytical Processing and data Mining technology, the composition and design of enterprise Decision Support System are put forward.
分析和论述了数据挖掘和联机分析处理的一般过程以及与此相关的一些技术。
Through analyze the general procedure of dada mining, OLAP and some other technique about them.
主要谈到的是数据仓库和数据集市、联机分析处理和数据挖掘以及前端展示技术。
The ones that spoke of mainly are data warehouse and the data mart, OLAP and data mining, and show technologies in the front-ends.
论文的主要工作如下：（1）对决策支持系统、数据仓库、联机处理分析OLAP、数据挖掘相关理论和技术进行了研究。
The paper's main tasks are as follows:(1) Some research was developed which was about the theory and technology of DSS, data warehouse (DW), Online Analytical Processing ( OLAP ) , data mining(DM).
商业智能的支撑技术包括数据仓库、联机分析处理和数据挖掘。
Data Warehouse, Online Analytical Processing and Data Mining constitute the supporting technology for BI.
伴随数据仓库技术出现的数据挖掘技术和联机分析处理OLAP技术又为数据分析提供了强有力的支持。
With the emergence of data warehouse, data mining technology and OLAP technology also come out. These two technologies provide the powerful support for data analysis.
文中详细介绍了客户关系管理系统、数据仓库、联机分析处理和数据挖掘技术。
The CRM system, the Data warehouse, the OLAP (online analysis processing) and the technology of Data Mining are introduced in detail in the paper.
本文主要利用数据仓库、联机分析处理技术和数据挖掘等多种技术构建潍坊网通的分析CRM系统，即经营分析管理子系统。
The paper introduces how to construct the Business analysis management in CRM by applying the Data Warehouse, On-Line Analytical Processing and Data Mining.
联机分析挖掘技术融合了联机分析处理技术和数据挖掘技术，成为决策支持应用系统新的技术依托。
The idea of using on-line analytical processing (OLAP) to access and analyze on-line monitoring data is presented.
摘要：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。
Absrtact: Introduces the main technology and system structure of business intelligence including data warehouse (DW), OLAP and data mining.
摘要：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。
Absrtact: Introduces the main technology and system structure of business intelligence including data warehouse (DW), OLAP and data mining.
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