大数据
分析
多样性(控制论)
重要事件
数据科学
劳动力
政府(语言学)
数据分析
计算机科学
工程类
业务
政治学
数据挖掘
历史
语言学
哲学
人工智能
考古
法学
作者
Leo H. Chiang,Bo Lu,Iván Castillo
标识
DOI:10.1146/annurev-chembioeng-060816-101555
摘要
Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.
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