论文标题:营销数据仓库模型的构建方法研究
The Research about the Method Marketing Data Warehouse"s Model"s Building
论文作者 李宝林
论文导师 黄光球,论文学位 硕士,论文专业 管理科学与工程
论文单位 西安建筑科技大学,点击次数 111,论文页数 69页File Size3548k
2004-05-01论文网 http://www.lw23.com/lunwen_47744592/ OLAP;营销组合;EDMA;数据钻取;数据聚合
OLAP;Marketing are made up;EDMA;Data are bored and fetched;The data are got together
数据仓库作为近年来发展迅速的一种新兴技术，它把收集到的数据转变成有意义的可用在分析和报表等应用程序中的信息。并且通过多部进程执行处理和分析，这些进程包括收集数据、净化数据和存储数据等。数据仓库是支持管理决策过程的、面向主题的、集成的、随时间而变得、持久的数据集合。数据仓库管理系统根据企业的原始数据和来自外部的数据汇集和整理成数据仓库，为企业提供完整、及时、准确和明了的商业决策支持信息。 本论文主要阐述营销数据仓库模型的建立过程。其包括六个大方面：第一部分主要阐述营销数据仓库的发展和现状。从数据仓库现状入手，着重说明了未来营销数据仓库的作用；第二部分主要介绍了营销数据仓库中所涉及的基本概念，其中主要包括一些基本概念和基本操作；第三部分主要是对营销数据仓库中数据的提取，营销数据仓库中的数据主要包括操作型营销数据库中的数据，这部分数据主要是根据一个基本营销公司的基本职能进行提取，和通常的进、销、存系统一样，本文给出了详细的流程和数据；另外营销数据仓库中的一部分数据来自于营销过程与其相关的主题，主要包括营销的四个基本步骤和几个基本主题(产品、客户、竞争对手)；本文的第四部分主要对营销数据仓库的企业级模型做一个比较详细的说明，通常，一个数据仓库的模型主要包括三个大的基本方面：概念模型、逻辑模型和物理模型。本章通过第三章的分析提取出了营销过程中相关的主题，并且对相应的主题做了细致的研究和分析。在此基础上综合描述了营销数据仓库的三大模型，并且给出了具体的ER图；论文的第五部分主要是从营销数据仓库的维度分入手，在OLAP的基础上提炼出了相关主题和过程的星形模式图。 总之，本论文从营销数据仓库的数据抽取、数据转移、数据迁移入手。在营销主题和操作职能方面全面阐述了营销数据仓库企业级模型。另外从维度和粒度入手，从顾客、产品、竞争对手和营销过程方面做了详细的分析。从而让我们在营销数据仓库方面有一个全面的、系统的了解。
The data warehouse is as developing a kind of fast new developing technology in recent years, itmake the collected data meaningful by using analysis and report form In the application programming.It is deal with and analyses through many parts of process the is it collect data,purify datum and storedatum,etc. To include to carry out. Data warehouse support to manage decision-making process,theme -oriented, become, lasting datum set with time that integrate. Data warehouse according to initialdata and come from external datum gather administrative system and put, offer the intact, prompt,accurate and commercial decision support information understood for enterprise. This thesis mainlyexplains the foundation about the data warehouse model of marketing. It includes six great respects:First part Explain the development of the data warehouse of marketing and current situation mainly.Proceed with warehouse current situation of the data, has stated the function of the data warehouse ofmarketing in the future emphatically; Second part Introduce marketing data basic conception involvedin the warehouse mainly, include some basic conception and basic operation mainly among them; Thethird part To marketing data abstraction of data of the warehouse mainly, marketing data of warehouseinclude marketing data of database of operating etc. mainly, the data to draw according to one basicmarketing basic function of Company mainly, with entering commonly, round pin, storing the systemthe samly, this text provides detailed procedure and data; Some data in the data warehouse ofmarketing come from the relevant theme in addition, a series of measures including the products ,taking in the customer, rival and marketing mainly; Make a more detailed explanation to the enterpriselayer model of the data warehouse of marketing mainly with fourth part of this text, usually, the modelof a datum warehouse includes three big basic respects mainly: Conceptual model, logic model andphysical model. This text is it happen marketing relevant theme of the course to draw through analysisof chapter three, and has made careful research and analysis to the corresponding theme. Havedescribed three major models of the data warehouse of marketing synthetically on this basis, andprovide concrete ER picture; Five part of thesis to is it spend from marketing data warehouse start with to link mainly, have refined out the relevant theme and star mode picture of the course on the basis of OLAP. Thesis this tell marketing data datum of warehouse collect, the data are shifted, the data are moved . Operate from marketing theme function explain the datum warehouse enterprise layer model of marketing in an all-round way in addition. Start with Unking degree with grain size in addition, has done the detailed explanation from customer, products, rival and sale course. Thus make us have an overall, systematic understanding in data warehouse of marketing.
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