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统计资料 国外会议统计 管理信息系统统计分析 amcis2005 文章排队.

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Presentation on theme: "统计资料 国外会议统计 管理信息系统统计分析 amcis2005 文章排队."— Presentation transcript:

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2 统计资料 国外会议统计 管理信息系统统计分析 amcis2005

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4 文章排队

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9 统计资料 国内会议统计 武汉 电子商务国际会议

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16 国内学者观点  Data-Intensive  Technology drive & model drive  陈禹, 中国人民大学

17  管理信息系统向三大方向发展 :  智能方向 : IDSS (Intelligent Decision Support System )Intelligent Decision Support System  集成方向 : CIMS 与 ERP  网络方向 : 电子商务  朱顺泉 朱顺泉  暨南大学管理学院 暨南大学管理学院 国内学者的观点

18  管理信息系统向三大方向发展 :  管理信息系统发展的网络化  系统开发方法的理性统一化  系统运行的智能化  黄梯云 黄梯云  哈尔滨工业大学 哈尔滨工业大学 国内学者的观点

19  管理信息系统向三大方向发展 :  管理信息系统发展的网络化  系统开发方法的理性统一化  系统运行的智能化  黄梯云 黄梯云  哈尔滨工业大学 哈尔滨工业大学 国内学者的观点

20  Return to the data:  information resource and index system  Data exchange system (XML)  Structured data and unstructured data 国内学者的观点

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22  1. Business Model and Technical Support  2. New Opportunities and New Challenges  3. Data-Intensive Computing  4. Strategies Technical trend

23 The development of MIS is a repeat process in which the Business Model and its Technique Tools push each other. Even the history of MIS is short, this progress is very obvious and fast. 1.Business Model and Technical Support

24 —— Main Language: COBOL —— Key Tech: Database —— Common Software: Lotus 1-2-3 —— Communicate: Local network —— Business Model: Centralized 、 ERP 、 MRP —— Key Word: Programming 80’s: Enterprise MIS

25 —— Main Language: C and C++ —— Key Tech: Networking —— Common Software: WINDOWS —— Communicate: INTRANNET —— Business Model: EDI 、 BPR —— Key Word: Integration 90’s: EC Started

26 —— Main Language: XML … —— Key Tech: Software Architect —— Common Software: eclipse —— Communicate:peer to peer 、 internet —— Business Model: SCM —— Key Word: Business Intelligence Now: EB move ahead

27 —— New trend needs New Tool —— New Tool Pushes New Model —— BI needs Data Centered Tech —— Data Centered Tech pushes BI New Model, New Tool

28 —— Data collective tech. as RFID —— Data transform tech. as wireless communication —— Data security tech. as digital signature —— Data analysis tech. as so-call data mining —— Data presentation tech. Relative Technology

29 New technology provided both new possibilities and new difficulties to managers, also both new opportunities and new challenges. 2. New Possibilities and Problems

30  —— More Space  —— More Speed  —— More choice  —— More data source New Possibilities

31  —— New market  —— New user  —— New service  —— New chanell  —— New tools New opportunities

32  —— Security  —— legal issues  —— cross cultural  —— social responsibilities New Problem

33  —— More risk and uncertainties, as a new business  —— New Technology, should be learn  —— Human Resource, training and retraining New Challenges

34  I believe that an new direction will attract more and more attention.  That is  Data-Intensive Computing 3. Data-Intensive Computing

35  “Communication of ACM” 2008,April,p30.  “Managing and processing exponentially growing data volumes, often arriving in time-sensitive streams from array of sensors and instruments, or at outputs from simulations; and  significantly reducing data analysis cycles so that researchers can make timely decisions.”  Data-Intensive Computing

36  1.metadata management technology  2.high performance computing platform  3.processor for network data stream  4.high reliability distributed file system Seven main topics

37  5. data handle system for wireless environment  6. fast data analysis tools  7. rapid security and signature processing tools Seven main topics (cont.)

38  Pay more attention on:  —— Data  —— Data Usage  —— Data Intensive Computing 4. Our Strategies

39  Technique change continues.  Innovation of Business model continues.  Our discussion and research also need continue. Not End


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