Real-time data analytics has become a critical tool in the retail sector, transforming decision-making and operational strategies. This review explores the practices of real-time data analytics in the USA and globally, highlighting how retailers use these technologies to gain insights into consumer behavior, optimize inventory management, and enhance customer experiences. In the USA, major retailers like Walmart and Amazon leverage real-time data analytics for personalized marketing, dynamic pricing, and efficient inventory management. Technologies such as RFID, IoT, and advanced analytics platforms enable real-time data processing, allowing retailers to respond swiftly to market changes. Globally, real-time data analytics is used for demand forecasting, predictive analytics, and supply chain optimization. Artificial intelligence and machine learning algorithms are increasingly integrated to analyze vast datasets, uncovering hidden patterns and predicting future market trends. Despite these benefits, challenges such as data privacy concerns, integration complexities, and the need for skilled professionals remain. The review emphasizes the importance of addressing these challenges to fully harness the potential of real-time data analytics. Future trends suggest a move towards more sophisticated applications of AI, increased use of IoT devices, and the integration of blockchain technology to enhance transparency and security. Retailers are also focusing on hyper-personalization, agile supply chains, and ethical, sustainable practices. The integration of real-time data analytics with retail practices is expected to deepen, fostering innovation and reshaping the industry's landscape. As technology continues to advance, the synergy between real-time data analytics and retail practices will play a crucial role in driving operational efficiency and customer satisfaction.Real-time data analytics has become a critical tool in the retail sector, transforming decision-making and operational strategies. This review explores the practices of real-time data analytics in the USA and globally, highlighting how retailers use these technologies to gain insights into consumer behavior, optimize inventory management, and enhance customer experiences. In the USA, major retailers like Walmart and Amazon leverage real-time data analytics for personalized marketing, dynamic pricing, and efficient inventory management. Technologies such as RFID, IoT, and advanced analytics platforms enable real-time data processing, allowing retailers to respond swiftly to market changes. Globally, real-time data analytics is used for demand forecasting, predictive analytics, and supply chain optimization. Artificial intelligence and machine learning algorithms are increasingly integrated to analyze vast datasets, uncovering hidden patterns and predicting future market trends. Despite these benefits, challenges such as data privacy concerns, integration complexities, and the need for skilled professionals remain. The review emphasizes the importance of addressing these challenges to fully harness the potential of real-time data analytics. Future trends suggest a move towards more sophisticated applications of AI, increased use of IoT devices, and the integration of blockchain technology to enhance transparency and security. Retailers are also focusing on hyper-personalization, agile supply chains, and ethical, sustainable practices. The integration of real-time data analytics with retail practices is expected to deepen, fostering innovation and reshaping the industry's landscape. As technology continues to advance, the synergy between real-time data analytics and retail practices will play a crucial role in driving operational efficiency and customer satisfaction.