An Overview of the Opportunities and Challenges of Data Analytics in Industry 4.0: Solutions for a Data-Driven Future in SMEs

Data analytics have become a cornerstone of modern industrial management, offering tools to maximize performance, optimize processes, and provide a competitive advantage. This paper presents a comprehensive overview of the opportunities and challenges of implementing data analytics in industrial management, with a particular focus on solutions tailored for small and medium-sized enterprises (SMEs). It addresses the critical role of data in decision-making, the integration of data analytics within the Industry 4.0 framework, and the complexities surrounding data management. Despite challenges like data complexity, integration issues, and security concerns, the paper proposes strategic solutions such as cost-effective data governance frameworks, scalable data integration platforms, and affordable cybersecurity measures, all tailored to the needs and constraints of SMEs. Utilizing a multi-method approach that combines literature review and case studies, the findings underscore the necessity for SMEs to adopt advanced yet accessible data analytics strategies and the outlined solutions to remain competitive in the industrial landscape.

Authors

Institutions

Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.07.017
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Overview of the Opportunities and Challenges of Data Analytics in Industry 4.0: Solutions for a Data-Driven Future in SMEs

J. R. Rios Leite, Eliana Abreu
Procedia Computer Science
Big Data and Business Intelligence
article

An Overview of the Opportunities and Challenges of Data Analytics in Industry 4.0: Solutions for a Data-Driven Future in SMEs

J. R. Rios Leite, Eliana Abreu
article en

Abstract

Data analytics have become a cornerstone of modern industrial management, offering tools to maximize performance, optimize processes, and provide a competitive advantage. This paper presents a comprehensive overview of the opportunities and challenges of implementing data analytics in industrial management, with a particular focus on solutions tailored for small and medium-sized enterprises (SMEs). It addresses the critical role of data in decision-making, the integration of data analytics within the Industry 4.0 framework, and the complexities surrounding data management. Despite challenges like data complexity, integration issues, and security concerns, the paper proposes strategic solutions such as cost-effective data governance frameworks, scalable data integration platforms, and affordable cybersecurity measures, all tailored to the needs and constraints of SMEs. Utilizing a multi-method approach that combines literature review and case studies, the findings underscore the necessity for SMEs to adopt advanced yet accessible data analytics strategies and the outlined solutions to remain competitive in the industrial landscape.

Procedia Computer ScienceVol. 263
Polytechnic Institute of Coimbra (PT), Research Center for Natural Resources, Environment and Society (PT), University of Coimbra (PT)
Industry, innovation and infrastructure
Openalex Percentile: Top 66%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.