"Smart Business Problems and Analytical Hints in Cancer Research" is a pioneering exploration of the intersection between data science, artificial intelligence, machine learning, and oncology. Delving into 25 advanced questions derived from real-world cancer research scenarios, this book offers comprehensive guidelines on leveraging data-driven methodologies to address key challenges in the field. From genomic profiling and patient data integration to tumor heterogeneity analysis and immunotherapy optimization, each question presents a nuanced case study accompanied by practical solutions. Through integrative analysis and predictive modeling, readers gain insights into personalized treatment strategies, biomarker discovery, and therapeutic response prediction. With a focus on innovation and impact, this book equips researchers, clinicians, and data scientists with the tools and techniques necessary to navigate the complex landscape of cancer analytics. By harnessing the power of data science and AI, "Smart Business Problems and Analytical Hints in Cancer Research" promises to revolutionize the future of oncology and improve patient outcomes worldwide.