A Self Learning Material Development on Hadoop Distributing Computing Platform

[[abstract]]現今資料從傳統結構化轉至半結構化、甚至非結構化，且數量正以極快速度地成長，巨大量資料已成為現階段一股新興潮流及關鍵競爭因子。在知識爆炸時代，如何從所蒐集的巨量資料來萃取知識，及利用巨量資料分析模型來提升競爭力、並展現價值，為協助各行各業提升效能、達到具競爭力的目標，巨量資料分析應用是主要關鍵。於此研究為自學教材開發，藉由文獻探討及資料蒐集，設計一份符合適用於分段、與環境限制下，自學的課程教材，實際應用在課堂上讓同學依開發之教材實作，學習Hadoop平台建置，提供一個實際之各式應用端分析工具平台建置，讓非資訊專業人士，能透過本論文提供之自學教材，建置符合所需之合適巨量資料分析工具平台，進而找尋巨量資料在其應用領域及機會。 本次研究取得兩梯次共31位人員，實作後所回收的結果並分析，確認使用此教材，讓學員對”了解巨量資料分析工具--Hadoop相關技術”具正向回應，另外分析出學員背景不同，所回應的要求也不盡相同，可作為後續研究。[[abstract]]Data nowadays has converted from being traditionally structured to semi-structured or even non-structured and its volume has been increasing rapidly Big data has become an emerging trend and critical competitive factor in the current stage In this era of information explosion ways on how to extract information from the collected big data and make use of big data analysis model to increase competitiveness and develop value so as to promote efficiency in every industry thereby achieving its competitive goals the application of big data analysis serves an important role This research is about the development of self-learning materials Through literature review and data collection this research designs a self-learning course material that is suitable for segmented and limited environment which can actually be used in classrooms allowing the students to make use of these developed learning materials for actual demonstration and learning the construction of Hadoop platform It also provides an actual platform installation of various analysis tool for end users thereby providing a self-learning material for non-professionals creating an appropriate big data analysis tool that satisfies needs and further look for possible opportunities and related field of application of big data The result of this research was gathered from the actual data from two batches of samples consisting of 31 participants Analysis confirms that there is a positive feedback with the use of these materials in “understanding big data analysis-Hadoop related techniques” Moreover analysis also shows that the provided demands differ in terms of student background and can be further explore