The Role of Azure Data Lake in Scalable and High-Performance Supply Chain Analytics

Growing complexity in global supply chains demands high- performance, scalable data management capabilities. Azure Data Lake offers a cloud-based platform wherein organizations can store, process, and analyze vast volumes of structured and unstructured data in a cost-effective manner. This study discusses how Azure Data Lake elevates supply chain analytics through the convergence of big data technologies, AI, and ML models. It is a mixed-method study, with case studies and statistical analysis being used for performance improvement measurement in supply chain activities. The main findings indicate that companies utilizing Azure Data Lake experience enhanced real-time decision-making, improved demand forecasting, and reduced inefficiencies in operations. However, challenges such as data protection and system integration persist. The paper concludes with sugges- tions for further research and strategies for optimizing Azure Data Lake utilization in supply chain analytics.