本文選題：大數據　切入點：技術運營　出處：《武漢紡織大學》2017年碩士論文　論文類型：學位論文

【摘要】：在互聯網時代,信息技術能力已經成為企業(yè)的核心競爭力之一,同時不同種類的數據也成為了企業(yè)的最寶貴資源。對于金融行業(yè)中的保險企業(yè)也不例外,隨著國民經濟的發(fā)展,人們對保險的認識越來越深,購買保險的需求也在不斷增加。那么如何能夠穩(wěn)定、高效的支撐起日益增長的業(yè)務,對于傳統保險企業(yè)的數據中心來說也是一項極大的挑戰(zhàn)。數據中心的價值不再是僅僅滿足于保證系統的穩(wěn)定運行,更重要的是如何將運行數據產生其應有的業(yè)務價值,達到降低成本、產生收益的效果。對保險企業(yè)數據中心而言從系統運維到技術運營的轉型對于數據中心價值的提升有著顯著的幫助。傳統企業(yè)數據中心的系統運維主要工作內容首先是把服務器、網絡、數據庫搭建好,然后把程序部署上去運行起來,再把相應的監(jiān)控加好,然后就開始等待告警和處理告警,或者是等待故障和處理故障的無序循環(huán)。其次是處理業(yè)務部門在使用系統中所遇到的種種問題,可以是系統缺陷導致的,也可以是因為不會使用導致的。對于運維工作的總結就是重復、等待、救火。對于運維人員來說其工作價值難以體現,沒有存在感,一旦出了問題開始質疑是否是運維工作的疏漏。對于數據中心的管理來說,同樣面對很高的挑戰(zhàn),高強度的工作崗位違背了傳統企業(yè)安逸舒適的一貫風格,但是獎懲制度、薪資待遇卻依然保持著傳統作風。造成高技能人才流失率大幅度提升,人員補充速度慢,從而進一步加重了在職人員的工作壓力。基于上述的業(yè)務挑戰(zhàn)和數據中心運維工作的困難,本文將依照國內某大型保險企業(yè)實際案例,研究其數據中心在遇到上述的業(yè)務挑戰(zhàn)以及管理上的困難后采取的相關措施,找到突破業(yè)務發(fā)展與數據中心運維難度間矛盾的方法,從技術與管理兩方面著手,逐步在高強度的工作壓力中建立起一套以大數據平臺為核心的自動化運維平臺,同時也產生了一套基于自動化的技術運營的管理體系。做到把運維工作前置,成功實現從系統運維向技術運營轉型。
[Abstract]:In the Internet era, the ability of information technology has become one of the core competitiveness of enterprises, at the same time, different kinds of data have become the most valuable resources of enterprises. The insurance enterprises in the financial industry are no exception, with the development of the national economy, People are getting more and more aware of insurance, and the demand for insurance is increasing. So how can we support the growing business steadily and efficiently? It is also a great challenge for the traditional insurance enterprise data center. The value of the data center is no longer just to ensure the stable operation of the system, but also how to generate its due business value from the running data. To reduce costs, For insurance enterprise data center, the transition from system operation and maintenance to technology operation is of great help to enhance the value of data center. The main contents of system operation and maintenance in traditional enterprise data center. First of all, the server, The network, the database are built up, and then the program is deployed to run, and then the corresponding monitoring is added, and then we start waiting for the alarm and handling the alarm. Or an out-of-order loop waiting for and dealing with a malfunction. The second is to deal with the problems encountered by the business department in using the system, which can be caused by a system defect. It can also be because it won't be used. The summary of the operation and maintenance work is repetition, waiting, and fire-fighting. To the operation and maintenance personnel, its work value is difficult to embody, and there is no sense of existence. Once something goes wrong, it starts to question whether it's an omissions in operations and maintenance. As for the management of data centers, it's also a challenge. High-intensity jobs run counter to the traditional corporate style of comfort and comfort, but rewards and penalties. The pay package, however, remains traditional. As a result, the rate of loss of highly skilled personnel has increased dramatically, and the rate of replacement has been slow. Based on the above business challenges and the difficulties in the operation and maintenance of the data center, this paper will be based on the actual case of a large insurance company in China. This paper studies the relevant measures taken by its data center after meeting the above business challenges and management difficulties, and finds a way to break through the contradiction between the business development and the operation and maintenance difficulty of the data center, and start from the two aspects of technology and management. At the same time, a set of automatic operation and maintenance platform with big data platform as the core, and a set of management system based on automation technology operation have been established step by step in the high intensity work pressure, so as to put the operation and maintenance work ahead of each other. Successfully realize the transformation from system operation and maintenance to technical operation.
【學位授予單位】：武漢紡織大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP311.13;F842.3

【參考文獻】

相關期刊論文 前4條

1 狄曉嬌;;Hadoop平臺的設計[J];通訊世界;2016年04期

2 白羽;;淺談數據中心的管理與建設[J];電子制作;2015年08期

3 李婷;;數據中心管理的新幫手——運維綜合管理系統[J];智能建筑;2015年02期

4 馮志強;;大數據時代網上書店信息運維和精準營銷[J];科技與出版;2015年01期

，

本文編號：1562303