Data management in industry: concepts, systematic review and future directions

Abstract Data management, particularly in industrial environments, is increasingly vital due to the necessity of handling ever-growing volumes of information, commonly referred to as big data. This survey delves into various papers to comprehend the practices employed within industrial settings concerning data management, by searching for relevant keywords in Q1 Journals related to data management in manufacturing in the databases of WebOfScience, Scopus and IEEE. Additionally, a contextual overview of core concepts and methods related to different aspects of the data management process was conducted. The survey results indicate a deficiency in methodology across implementations of data management, even within the same types of industry or processes. The findings also highlight several key principles essential for constructing an efficient and optimized data management system.

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Publication Details

Journal
Journal of Intelligent Manufacturing
Published
2025-02-15
DOI
https://doi.org/10.1007/s10845-025-02570-z
Citations
4
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
9.14

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article

Data management in industry: concepts, systematic review and future directions

André Dionísio Rocha, Nelson Freitas, José Barata
4 citations
Journal of Intelligent Manufacturing
Big Data and Business Intelligence
9.14
article

Data management in industry: concepts, systematic review and future directions

André Dionísio Rocha, Nelson Freitas, José Barata
article en
4 citations

Abstract

Abstract Data management, particularly in industrial environments, is increasingly vital due to the necessity of handling ever-growing volumes of information, commonly referred to as big data. This survey delves into various papers to comprehend the practices employed within industrial settings concerning data management, by searching for relevant keywords in Q1 Journals related to data management in manufacturing in the databases of WebOfScience, Scopus and IEEE. Additionally, a contextual overview of core concepts and methods related to different aspects of the data management process was conducted. The survey results indicate a deficiency in methodology across implementations of data management, even within the same types of industry or processes. The findings also highlight several key principles essential for constructing an efficient and optimized data management system.

Journal of Intelligent ManufacturingVol. 37(2)
Universidade Nova de Lisboa (PT)
Universidade Nova de Lisboa, Fundação para a Ciência e a Tecnologia
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Big Data and Business Intelligence
9.14
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