Big Data Analytics in IoT-Integrated Strategic Inventory Systems

Abstract

The integration of Big Data Analytics (BDA) with the Internet of Things (IoT) has revolutionized strategic inventory systems, enabling real-time decision-making and enhanced operational efficiency. This research explores the transformative impact of BDA in IoT-integrated inventory systems by analyzing data streams from connected devices, sensors, and supply chain networks. The study investigates how predictive analytics, machine learning algorithms, and data visualization techniques optimize stock levels, reduce operational costs, and improve demand forecasting accuracy. Key challenges such as data security, scalability, and interoperability are also examined. The findings highlight the significance of advanced analytics in achieving smarter, more agile, and sustainable inventory management strategies, offering valuable insights for businesses seeking a competitive edge in dynamic markets.

Keywords: Big Data Analytics, Internet of Things (IoT), Strategic Inventory Systems, Predictive Analytics, Machine Learning, Real-time Decision-making, Supply Chain Optimization, Data Security, Demand Forecasting, Operational Efficiency