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Data Disaster Recovery Study Of A Rail Transportation Equipment Co., LTD

Posted on:2013-12-04Degree:MasterType:Thesis
Country:ChinaCandidate:L J ZangFull Text:PDF
GTID:2248330374982297Subject:Business Administration
Abstract/Summary:PDF Full Text Request
In recent years, the application of IT in all walks of life become more and more widely, the dependence by the enterprises are getting more intense, at the same time, the attention of business sustainable need is higher than ever. In many industries, interrupt cost is daunting and devastating, How to better ensure enterprise data security has become a consensus of the enterprise. This depends on a good enterprise data disaster recovery strategies and mechanisms for planning, from disk or system failure recovery or, in extreme cases, to recovery from the destruction of the data center fire or flood.This study is based on Bombardier Sifang (Qingdao) Transportation Co., LTD. As a systems administrator, from the point of view of the depth of the disaster analyzes reasons, we found many of them are not caused by disaster itself complex problems, the bigger problem lies in the cognitive for the disaster is low, not enough attention, management confusion. We set up the scientific classification for the disasters firstly in the following chapters, and then the targeted setting to the classification, so as to establish the enterprise Data Disaster Recovery System.This study will convert disaster recovery from the traditional approach "to be redundant, restore data after the disaster happened" to a more active attitude "let enterprise do redundancy, to prevent disaster, guarantee the continuity of the enterprise data services". This change will embody in the information industry and enterprise, the continued available data services on the BST property and even the enterprise’s existence shows vital significance.According to papers’background,research purpose and significance, and the method of research, this paper is divided into six chapters.Firstly, on the basis of topic selection, this thesis introduces the background and significance, and puts forward the research paper thoughts, research methods and innovations.The second chapter generally introduce the theory and technology when building the BST data tolerant system, this paper expounds the importance of these theories and the help of the whole system.The third chapter provides two data analysis tolerant examples, this paper expounds the management and the dealing with problems, these problems may lead to losses, what we should learn from the experience and lesson? and make a analysis combined with actual enterprise’s BST situation. According to these two examples, what lessons can be drawn by BST? The fourth chapter introduces how software does analysis, backup software technology selection in data structures tolerant system according to the experience. Chapter5talks about the reasonable classification to disaster, and how to take respective measures according to the classification, and explains the implementation to BST tolerant system in detail.The sixth chapter closing, points out that the conclusion of this paper, outlook and the future research direction.The innovation of this paper mainly reflects in:(1).Based on network, disk array, VMWare, Exchange and related theory, combined with the practical situation of businesses, the paper analyzes the enterprise IT and development situation, also design the suitable backup strategy and tolerant mechanism by the case analysis.(2).For the first time to classify the disaster to prevent/do not prevent, low probability high grade and high probability low grade classification method, and the design the processes to classified disaster.(3). IT rarely see a data disaster recovery of the various application systems integrate information, this paper analyzes and does some research about all kinds of enterprise’application system of data disaster recovery needs, which concludes the significant demonstration.
Keywords/Search Tags:enterprise data disaster recovery, data backup, disaster classification, data tolerant system construction
PDF Full Text Request
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