English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51296/86402 (59%)
Visitors : 8162495      Online Users : 87
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/105520


    Title: 巨量資料運用於流通業商業智慧系統發展佈局之研究
    Other Titles: A study of applying big data to the development and layout of business intelligence system for the retailing industry
    Authors: 陳協慶;Chen, Hsieh-Ching
    Contributors: 淡江大學資訊管理學系碩士班
    蕭瑞祥;Shaw, Ruey-Shiang
    Keywords: 巨量資料;商業智慧系統;流通業;Big Data;Business Intelligence;Retailing Industry
    Date: 2015
    Issue Date: 2016-01-22 14:58:09 (UTC+8)
    Abstract: 流通業界在面對系統資料越來越龐大,如何在原已建置或即將建置的商業智慧系統(BI)之基礎上,結合巨量資料之新觀念,以延續商業智慧系統的生命週期與未來發展,為目前流通業界重要的議題。
    本研究旨在探討流通業在建置商業智慧系統後,如何以商業智慧為基礎延伸應用巨量資料的概念,進而如何整合巨量資料之理論以維持商業智慧系統的價值。本研究先經文獻分析探究流通業與巨量資料的定義,進而發展一雛型系統,再運用專家訪談之研究方法蒐集流通業導入意願及現況問題。專家使用雛型系統後,經訪談彙總出的建議結果:流通業界應使用巨量資料的概念,延伸發展商業智慧系統,流通業界可使用RFM(Recency Frequency Monetary)模型了解顧客貢獻以及流通業可使用巨量資料的資料價值化定義來產生新的獲利模式。本研究成果可提供流通業界利用巨量資料建置商業智慧系統之參考。
    The retailing industry when facing the growing large volume of system data, how to integrate the novel big data concept with the existing business intelligence (BI) system or BI system about to establish; and how to expand the BI system’s life cycle and its further development became an essential issue.
    The research aims to discuss how the retailing industry extend the application of the big data concept after BI-system been established and further integrate the big data theories to maintain the value of existing BI systems. A prototype system was developed after literature analysis of the definitions of “Retailing Industry” and “Big Data”. And then the expert interview method was adopted to find the intention and status quo of the industry on big data application. After the prototype system been trailed by the experts, it is summarized and suggested that: 1. the retailing industry shall utilize the big data concept to extend BI systems; 2. RFM (Recency Frequency Monetary) model can be used to evaluate customers’ attribution; and 3. the data value definition of big data can be used to generate new profit modes. The research achievements can be provided to the retailing industry as references to apply big data in BI system establishment.
    Appears in Collections:[資訊管理學系暨研究所] 學位論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML61View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback