The article "Real-time data analytics in retail: A review of USA and global practices" by Mustafa Ayobami Raji et al. explores the significant impact of real-time data analytics on the retail sector, both in the USA and globally. The study highlights how real-time data analytics has revolutionized decision-making and operational strategies, enabling retailers to gain deeper insights into consumer behavior, preferences, and market trends. Key applications include personalized marketing campaigns, dynamic pricing strategies, and efficient inventory management. Technologies such as RFID, IoT devices, and advanced analytics platforms have facilitated seamless data flow, allowing retailers to respond swiftly to market changes. In the USA, retail giants like Walmart and Amazon have leveraged real-time data analytics to enhance customer experiences and operational efficiency. The integration of these technologies has led to improved security, service quality, and strategic decision-making. However, challenges such as data privacy concerns, integration complexities, and the need for skilled professionals are acknowledged. On a global scale, diverse retail markets have embraced real-time data analytics to stay competitive. Cross-border e-commerce and online marketplaces have intensified the need for real-time insights, with retailers using predictive analytics to forecast demand, reduce stockouts, and streamline supply chain operations. The integration of artificial intelligence and machine learning algorithms has further enhanced the ability to analyze large datasets and predict future market trends. The article also discusses future trends and innovations, including the increasing integration of AI and ML, the rise of edge computing, and the potential of 5G technology. These advancements are expected to drive hyper-personalization, agile supply chains, and a commitment to ethical and sustainable business practices. The authors recommend that retailers invest in advanced technologies, prioritize data security and privacy, foster collaboration between IT, data science, and business teams, and embrace sustainable and ethical practices. In conclusion, the article emphasizes the transformative impact of real-time data analytics on the retail sector, highlighting its role in enhancing customer experiences and operational efficiency. The successful integration of real-time data analytics requires a holistic approach that combines advanced technologies, ethical practices, and a skilled workforce. As the retail industry continues to evolve, effective use of real-time data analytics will be crucial for retailers to thrive in a data-driven future.The article "Real-time data analytics in retail: A review of USA and global practices" by Mustafa Ayobami Raji et al. explores the significant impact of real-time data analytics on the retail sector, both in the USA and globally. The study highlights how real-time data analytics has revolutionized decision-making and operational strategies, enabling retailers to gain deeper insights into consumer behavior, preferences, and market trends. Key applications include personalized marketing campaigns, dynamic pricing strategies, and efficient inventory management. Technologies such as RFID, IoT devices, and advanced analytics platforms have facilitated seamless data flow, allowing retailers to respond swiftly to market changes. In the USA, retail giants like Walmart and Amazon have leveraged real-time data analytics to enhance customer experiences and operational efficiency. The integration of these technologies has led to improved security, service quality, and strategic decision-making. However, challenges such as data privacy concerns, integration complexities, and the need for skilled professionals are acknowledged. On a global scale, diverse retail markets have embraced real-time data analytics to stay competitive. Cross-border e-commerce and online marketplaces have intensified the need for real-time insights, with retailers using predictive analytics to forecast demand, reduce stockouts, and streamline supply chain operations. The integration of artificial intelligence and machine learning algorithms has further enhanced the ability to analyze large datasets and predict future market trends. The article also discusses future trends and innovations, including the increasing integration of AI and ML, the rise of edge computing, and the potential of 5G technology. These advancements are expected to drive hyper-personalization, agile supply chains, and a commitment to ethical and sustainable business practices. The authors recommend that retailers invest in advanced technologies, prioritize data security and privacy, foster collaboration between IT, data science, and business teams, and embrace sustainable and ethical practices. In conclusion, the article emphasizes the transformative impact of real-time data analytics on the retail sector, highlighting its role in enhancing customer experiences and operational efficiency. The successful integration of real-time data analytics requires a holistic approach that combines advanced technologies, ethical practices, and a skilled workforce. As the retail industry continues to evolve, effective use of real-time data analytics will be crucial for retailers to thrive in a data-driven future.