Enhancing Supply Chain Integration through Data Engineering: Frameworks and Applications
DOI:
https://doi.org/10.32628/CSEIT251112229Keywords:
Data Engineering, Digital Transformation, Supply Chain Integration, Supply Chain Management, Supply Chain OptimizationAbstract
This comprehensive article explores the intersection of data engineering and supply chain integration (SCI), examining how modern technological frameworks transform traditional supply chain operations. The article investigates the critical components of successful supply chain integration, including data consolidation, interoperability, real-time visibility, and predictive analytics. Through detailed analysis of implementation frameworks, applications, and challenges, the article demonstrates how data engineering serves as a foundational enabler for enhanced supply chain performance. The article examines various case studies across retail, manufacturing, and logistics sectors, highlighting practical applications and outcomes. Furthermore, it addresses emerging technologies such as blockchain, artificial intelligence, edge computing, and digital twins, providing insights into future directions of supply chain integration. The article contributes to both theoretical understanding and practical implementation of data engineering in supply chain management, offering valuable insights for organizations seeking to achieve operational excellence in increasingly complex business environments.
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