The Role of Big Data in Engineering Management: A Review of Analytical Techniques and Applications

Abstract

The integration of big data into engineering management has significantly transformed the field, offering advanced analytical techniques that enhance decision-making processes across various domains. This narrative review explores the role of big data in engineering management, focusing on its applications in project management, supply chain management, asset management, quality control, and sustainability. Descriptive, predictive, and prescriptive analytics are examined in detail, highlighting their methodologies and practical applications. The review also addresses the challenges associated with data management, ethical concerns, and the skills required to effectively leverage big data in engineering contexts. Future research directions are identified, emphasizing the potential of emerging technologies like artificial intelligence, the Internet of Things, and blockchain in enhancing big data analytics. The findings suggest that while big data offers substantial benefits, its successful implementation requires addressing significant challenges and equipping professionals with the necessary skills. The review contributes to a deeper understanding of how big data can be harnessed to improve engineering management practices and outlines pathways for future exploration.