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| Title: | 金融業與網路科技業導入巨量資料系統的關鍵因素之個案研究
Case Studies of Key Factors for implementing Big Data system on Financial and Internet Technology Industries |
| Authors: | 陳冠廷
Chen, Kuan Ting |
| Contributors: | 吳豐祥
沈錳坤
Wu, Vincent
Shan, Man Kwan
陳冠廷
Chen, Kuan Ting |
| Keywords: | 金融業
網路科技業
巨量資料
關鍵因素
Financial Industry
Internet Technology
Big Data
Critical Factors |
| Date: | 2015 |
| Issue Date: | 2015-10-01 14:29:54 (UTC+8) |
| Abstract: | 隨著網際網路的普及，智慧型手機與物聯網開始興起，根據資策會的調查，台灣約有49.5%的智慧型手機占有率，大約每2人就有一人擁有智慧型手機，而物聯網的興起，製造了大量的數據與資料，而這些數據與資料透過不同的處理方式，可帶給企業不同的商業智慧與洞見，而傳統產業因此面臨了巨大的轉變與挑戰，優步(Uber)就是改變傳統計程車產業與物聯網的一個例子，顧客不再需要招手才能搭上計程車，靠著網路、手機APP與GPS定位系統即可獲知車輛資訊、到達時間與聯絡司機，而優步可掌握乘客資訊、行車路線與顧客服務。不僅僅是計程車產業，亞馬遜的崛起也代表了傳統零售業的轉變，因此如何面對巨量資料對傳統企業都將是一項挑戰。
巨量資料的導入與分析可以提供企業掌握消費者行為，也可透過數據分析研發新服務與產品，此研究從三方面來探討金融產業與網路科技業導入巨量資料系統的關鍵因素，分別為導入流程、企業本身與巨量資料系統，另外藉由三家個案公司訪談，並輔以文獻所探討的研究架構來進行驗證”金融業與網路科技業導入巨量資料的流程為何?”、”金融業與網路科技業導入巨量資料時的關鍵因素?”、” 金融業與網路科技業導入巨量資料後有何優勢?”
本研究最後發現，金融業與網際網路業導入巨量資料分成三個階段，首先企業會先詮釋自身對巨量資料之定義，定義自身巨量資料之意義後，企業會開始集體研討導入流程，依照自身對巨量資料的詮釋來集體擬定對企業最好的導入流程，此階段通常會是三階段中耗時最長，也需做許多內外部研究、規劃與管理。最後一階段為實做階段，企業會依照集思廣益後所擬定出的計畫來完成巨量資料的導入。而本研究透過個案訪談也發現七項導入巨量資料之關鍵因素，包含，導入隊伍的組成、高層管理者的支持、導入時機、巨量資料系統的選擇、明確的目標與策略、內外部員工訓練與支援。最後企業運用第三方與開放式資料軟體來處理巨量資料使企業更了解顧客需求與運用於新產品研發。
With the popularity of internet, smart phones and Internet of Things begin to emerge. According to Institute for Information Industry, there are approximately 49.5% of smart devices in Taiwan, which mean every two people will own at least one smart device. In addition, more devices are connected to the internet. Therefore, tremendous amount of data is created and increased exponentially. With applicable and correct techniques, Big Data can provide valuable insight and business intelligent. Traditional industries are forced to change. For example, Uber is one innovative idea that changes the ways people ride taxi. Riding taxi become more efficient and effective with Uber.
This research explores critical factors of Big Data implementation on financial and internet technology industries from three perspectives. This includes key processes of the Big Data implementation, enterprises factors, and the Big Data system. Moreover, literature review was conducted to. In addition, three case studies were interviewed and analyzed based on research framework. Lastly, three research questions are answered. First, what are the key process for financial and internet technology industries implementing the Big Data system? Second, what are the critical factors for financial and internet technology industries implementing the Big Data system? Third, what are the potential benefits after the Big Data implementation?
The research findings are primarily categorized into two parts. First, there are three phases of financial institution and internet technology industries implementing the Big Data system. The three phases included defining, brainstorming and implementation phases. The three phases are described below:
1. Defining Phase: Companies will first define their own interpretation of Big Data in order to plan and coordinated their implementation.
2. Brainstorming Phase: Companies averagely spent most of the time in this phase. The implementation team leads must brainstorm to find the best way to enforce and carry out the Big Data project by searching, organizing and surveying internal and externally.
3. Implementation Phase: Companies follow their previous made proposal steps by steps.
This research also concluded and found several critical factors during the Big Data implementation. The critical factors included but not limited to:
1. An implementation team regardless the size to carry out the Big Data project
2. Top management’s commitment on implementation
3. Timing on the implementation
4. Big Data system selection
5. Clear goals and objectives |
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| Description: | 碩士
國立政治大學
科技管理與智慧財產研究所
102364139 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0102364139 |
| Data Type: | thesis |
| Appears in Collections: | [科技管理與智慧財產研究所] 學位論文
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