本文選題：數據庫營銷 + 云計算　； 參考：《浙江理工大學》2013年碩士論文

【摘要】：互聯網的應用與發(fā)展不僅促進了各個新興產業(yè)的產生與發(fā)展，影響了每個人的生活，同時也為傳統制造業(yè)提供了機遇與挑戰(zhàn)。對于制造業(yè)企業(yè)來說，常規(guī)的營銷方式，如投放廣告、搞促銷活動等方式已經遠遠不能滿足他們需要。常規(guī)營銷方式的制定往往需要通過較長的周期及過高的成本收集客戶數據然后人工分析，再制定相應的營銷策略與方式，甚至在缺少數據的情況下盲目進行營銷策略的制定，所以很難達到企業(yè)預期的效果。而通過數據庫營銷，企業(yè)可以方便地收集和積累客戶信息，構建龐大的顧客信息庫，然后通過云計算技術對海量數據快速準確地篩選和分析，從而有效地進行客戶數據挖掘與關系維護。本文提出了基于Hadoop云的數據庫營銷系統的架構，實現海量數據的處理與存儲，，并將其應用到紅塔集團數據庫營銷系統中，并且在系統初步完成并投入運行后，紅塔集團卷煙銷量尤其重點促銷品牌銷量相比同期的有了大幅度提升，數據庫營銷在其中起了至關重要的刺激作用。文章主要研究內容如下： 1）分析紅塔集團的現狀，完成紅塔集團數據庫營銷系統的需求分析，根據需求分析，針對性地對Hadoop分布式計算平臺進行研究和綜述，了解其優(yōu)勢、架構和運行機制，分析使Hadoop構建紅塔集團企業(yè)私有云的可行性。 2）探討了數據庫營銷常用數據挖掘方法，并根據紅塔集團數據庫營銷系統的實際需求及首要目標，構建了促銷活動響應模型，提高集團促銷活動客戶響應率；構建促銷活動決策模型，為決策者提供有效的客戶信息，確定促銷產品及促銷客戶群；設計了客戶終身價值、客戶忠誠度計算方法，構建客戶忠誠度預警模型以及客戶忠誠度提升模型。 3）研究設計Hadoop與關系型數據庫協同工作方案，設計Hadoop分布式平臺下MapReduce計算模型對關系型數據的處理方法，并設計使用最優(yōu)數據集選擇算法構建MapReduce Job數據流，實現通用性設計，降低維護成本。 4）根據紅塔集團的實際情況，給出了系統總體設計方案，并應用Hadoop構建紅塔集團企業(yè)私有云。
[Abstract]:The application and development of the Internet not only promote the emergence and development of each new industry, but also provide opportunities and challenges for the traditional manufacturing industry.For manufacturing enterprises, conventional marketing methods, such as advertising, promotional activities and so on, are far from meeting their needs.The formulation of conventional marketing methods often needs to collect customer data through a long period and too high cost, then manually analyze, and then formulate corresponding marketing strategies and methods, even blindly make marketing strategies in the case of lack of data.So it is difficult to achieve the desired results.Through database marketing, enterprises can easily collect and accumulate customer information, build a huge customer information base, and then quickly and accurately screen and analyze massive data through cloud computing technology.In order to effectively carry out customer data mining and relationship maintenance.In this paper, the architecture of database marketing system based on Hadoop cloud is put forward, which realizes the processing and storage of massive data, and applies it to the database marketing system of Hongta Group, and after the system is initially completed and put into operation,Hongta Group's cigarette sales, especially focused on the promotion of brand sales compared with the same period has a significant increase, database marketing has played a vital role in the stimulus.The main contents of this paper are as follows:1) analyzing the current situation of Hongta Group, completing the requirement analysis of Hongta Group's database marketing system, researching and summarizing the Hadoop distributed computing platform according to the requirement analysis, understanding its advantages, structure and operation mechanism.This paper analyzes the feasibility of Hadoop to construct private cloud of Hongta Group.2) the common data mining methods of database marketing are discussed, and according to the actual demand and primary goal of the database marketing system of Hongta Group, the response model of promotional activities is constructed to improve the customer response rate of group promotional activities.The decision model of promotion activities is constructed to provide effective customer information for decision makers, to determine the promotion products and customer groups, and to design a method for calculating customer lifetime value and customer loyalty.Build customer loyalty warning model and customer loyalty promotion model.3) study and design the cooperative work scheme between Hadoop and relational database, design the method of MapReduce computing model to deal with relational data under Hadoop distributed platform, and design the MapReduce Job data stream using the optimal data set selection algorithm to realize the universal design.Reduce maintenance costs.4) according to the actual situation of Hongta Group, the overall design scheme of the system is given, and the private cloud of Hongta Group Enterprise is constructed by using Hadoop.
【學位授予單位】：浙江理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP311.13

【參考文獻】

相關期刊論文 前10條

1 楊浩;;基于網絡環(huán)境中數據庫營銷的應用研究[J];辦公自動化;2011年10期

2 黃佳進,劉椿年,李文斌;市場值函數挖掘的研究和實現[J];北京工業(yè)大學學報;2003年01期

3 劉椿年,萇彩卿,黃佳進,歐創(chuàng)新;基于Boosting的市場值函數算法及其評價[J];北京工業(yè)大學學報;2004年03期

4 薛志強;劉鵬;文艾;周游;許闖;;分布式文件系統管理策略研究[J];電腦知識與技術;2011年01期

5 張華強;;關系型數據庫與NoSQL數據庫[J];電腦知識與技術;2011年20期

6 程瑩;張云勇;徐雷;房秉毅;;基于Hadoop及關系型數據庫的海量數據分析研究[J];電信科學;2010年11期

7 孫慶波;孟偉;孫宇;;基于交叉銷售模型的客戶聚類研究[J];福建電腦;2008年04期

8 江務學;張t

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