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Abstract The blood banking industry is a cornerstone of modern healthcare, thus playing a vital role in the collection, testing, processing, and distribution of blood and blood products. The primary objective of blood banks is to ensure a steady supply of safe and compatible blood for patients in need, whether for surgeries, trauma care, chronic conditions, or other medical treatments. As the demand for blood continues to grow due to an aging population, advances in medical treatments, and increased healthcare access, the challenges faced by the blood banking industry become more pronounced (Smith, 2020). Given the perishable nature of blood and the complexities involved in its collection, storage, and distribution, data analytics has emerged as an essential tool to optimize these processes. The application of data‑driven insights improves operational efficiency, enhances donor recruitment and retention, minimizes waste, and ensures compliance with regulatory requirements (Duan & Xiong, 2015). Data analytics emerges as a powerful tool that can transform the way blood banks operate, making their processes more efficient, accurate, and responsive. Blood banks must navigate a complex landscape of supply chain management, donor recruitment, inventory control, and regulatory compliance while maintaining the highest standards of safety and quality. This chapter explores the role of data analytics in the blood banking industry, highlighting its impact on supply chain management, predictive modeling, donor behavior analysis, quality assurance, and emerging technologies, and how blood banking can be a trained occupation for younger generations around the world.