Big data analytics opportunities for applications in process engineering
| Autor: | Mitra Sadat Lavasani, Nahid Raeisi Ardali, Rahmat Sotudeh-Gharebagh, Reza Zarghami, János Abonyi, Navid Mostoufi |
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| Rok vydání: | 2021 |
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| Zdroj: | Reviews in Chemical Engineering. 39:479-511 |
| ISSN: | 2191-0235 0167-8299 |
| Popis: | Big data is an expression for massive data sets consisting of both structured and unstructured data that are particularly difficult to store, analyze and visualize. Big data analytics has the potential to help companies or organizations improve operations as well as disclose hidden patterns and secret correlations to make faster and intelligent decisions. This article provides useful information on this emerging and promising field for companies, industries, and researchers to gain a richer and deeper insight into advancements. Initially, an overview of big data content, key characteristics, and related topics are presented. The paper also highlights a systematic review of available big data techniques and analytics. The available big data analytics tools and platforms are categorized. Besides, this article discusses recent applications of big data in chemical industries to increase understanding and encourage its implementation in their engineering processes as much as possible. Finally, by emphasizing the adoption of big data analytics in various areas of process engineering, the aim is to provide a practical vision of big data. |
| Databáze: | OpenAIRE |
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