The deep integration of digital technologies has ushered biomedical science into a new era driven by data, making biomedical big data a cornerstone for precision medicine, medical research innovation, and public health prevention and control. Compared to traditional medical data, modern biomedical big data is characterized by multimodality, high dimensionality, and strong interconnectivity, fundamentally transforming conventional empirical and fragmented approaches to research and clinical practice. This paper systematically reviews the current applications of biomedical big data from key medical use cases, analyzes existing challenges in data governance, technological integration, and ethical compliance, moves beyond superficial generalizations, and identifies the main development directions of the field across three dimensions: technological evolution, clinical translation, and system building. It provides theoretical support for the standardized application, industrial implementation, and advancement of biomedical big data in the medical domain.