The concept of big data (BD) encompasses the management and analysis of vast, complex datasets that are difficult to handle with traditional database tools. Initially defined by three primary attributes—volume, velocity, and variety—it now includes veracity, referring to data quality, and value, which pertains to the utility derived from data. The healthcare system is a complex multidimensional system, where the use of large datasets dates back to the early registration of patient data and medical research. Recently, the amount of information generated has risen exponentially, mainly from new sources, such as biosensors and patient social networks. However, the main challenge remains the integration and analysis of a large amount of complex heterogeneous data, requiring new tools, methods, and technologies, such as data mining, predictive analytics, and insight analytics. In the healthcare sector, BD offers several benefits such as enhanced diagnostics, personalized treatments, and the ability to address systemic challenges and inefficiencies. At the same time, its use also raises significant ethical concerns, such as privacy issues, accountability, and the societal impact of data-driven decisions. As BD technology evolves, it is essential to adopt responsible practices grounded in ethical frameworks and to integrate lessons learned from previous implementations. This chapter focuses on the evolution of BD technology, its applications, and benefits in health care as well as lessons learned regarding implementations, and ethical issues that need to be considered. Finally, it discusses the future perspective of this technology.