大數據解析已成近年來相當熱門的話題，各領域皆試著把新思維帶入企業中，以提升營收或是找到潛在模式。大數據解析的基礎建立於大量、多樣化、快速產生的數據量以及其準確性，並且需要搜集、分析、應用才能展現它的價值。航空業對於數據產生、保存上更是鉅細靡遺，被法規和相關手冊嚴格規範，若能更妥善利用這些數據，將會使得航空業成為更安全、更有效率的產業。
基於CRISP-DM(Cross Industry Standard Process for Data Mining)，本論文將這套已發展成熟並廣泛利用的架構利用於航空業，初步探討大數據解析之思維。由於航空業瞬息萬變，數據解析又是針對個案研究，一套通用的程序可以讓分析師面對各種狀況時具備數據解析思維。本論文以引擎壽命預測做為範例，將引擎感測器產生的數據進入數據解析程序並探討，找出其隱藏價值。
人類的判斷力與直覺，配合數據解析的客觀性，將成為強而有力的洞見。

Big data analysis has become a very popular topic recently. In various fields are trying to bring the new insight into their enterprise for increasing revenue or finding potential patterns. Furthermore the airline can seek new way to serve the marketplace and increase their profit, balancing both safety and revenue. Basis for big data analysis is on the volume, variety, velocity, and veracity of data. It needs to be well collected, analyzed, and applied that can reveal its value. For aviation, there is a strict regulation for collecting, preserving data, but most of the data are not well used.
In this study, based on CRISP-DM, a robust and well-proven data mining methodology, as the fundamental concept to create a data analytic processing which is suitable for aviation. A generic data thinking can help analysts to handle with diversified data type, a variety data source, and different analyzing software. We focus on the procedure that gives aviation analysts a logical and data thinking. The purpose of this study is to create a preliminary approach of aviation data analytic, because there is not a standard operation procedure yet. However, data analytic is a case by case study, it is impossible to have an all-powerful tool which is able to analyze every database. An engine sensor database is used in this procedure to give example for data thinking and investigating. Try to find hidden information to reveal its value.
Bringing big data analytic into aviation safety system does not mean to exclude experts' opinion. Human work with data can generate great insights.

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