資料解析的方法介紹
(Introduction to Data Analytics)

工程資料(Engineering data)在企業關鍵系統(business-critical systems)及應用變得愈來愈重要。聲音、影像、即時視頻、動作、機器性能的公制單位、以及其他感測器產生的資料,未來將會與企業、交易以及其他的IT資料結合,以對複雜的現象進行更精密的分析。除此之外,資料的大小也將帶來許多不同的挑戰;比方說,記憶體不足、處理時間過長、或資料產生太快來不及儲存等等。標準的演算法通常不是為了在合理的時間及記憶體空間下處理龐大資料集而設計的。

在本演講中,您將學會利用MATLAB®及技巧來處理這些挑戰。本演講將聚焦於一般性的方法,接下來的演講中,將對特定的工程資料類型進行詳細的介紹。

In this session you will learn approaches and techniques available in MATLAB® to tackle these challenges. We will focus on general approaches in this talk and specialize into specific types of engineering data in later sections.

Engineering data have become essential in business-critical systems and applications. Audio, image, real-time video, motion, machine performance metrics, and other sensor-generated data are being combined with business, transactional, and other IT data to create opportunities for sophisticated analytics on more complex phenomena. In addition, the size of the data sets may present challenges such as lack of available memory, taking too long to process, or streaming too quickly to store. Standard algorithms are usually not designed to process big data sets in reasonable amounts of time or memory.