Big Data Concept

  Introduction The healthcare industry is undergoing a data revolution, with vast amounts of information generated from electronic health records (EHRs), genomic sequencing, medical imaging, and wearable devices. Big data analytics has become essential for extracting actionable insights from these complex datasets. However, traditional computing methods often struggle with the scale and complexity of healthcare data. Quantum computing, with its ability to perform complex calculations at unprecedented speeds, offers a transformative approach to big data analytics in healthcare. This chapter explores how quantum computing enhances big data processing in healthcare, focusing on its principles, applications, benefits, and challenges. The Role of Big Data in Healthcare Big data in healthcare encompasses diverse datasets, including: Electronic Health Records (EHRs) : Patient demographics, medical histories, and treatment records. Genomic Data : DNA sequences and gene expression profil...

  Introduction In the rapidly evolving landscape of healthcare, big data has emerged as a transformative force, enabling unprecedented insights into patient care, disease management, and operational efficiency. Defined by its volume, variety, velocity, and veracity, big data encompasses vast datasets from electronic health records (EHRs), wearables, genomic sequencing, and more, generating over 2,314 exabytes daily by 2025. This chapter explores how big data is revolutionizing patient care, from predictive analytics to personalized medicine, while addressing benefits, challenges, and future trends. As of 2025, integrations of artificial intelligence (AI) and big data analytics are not only improving outcomes but also bridging gaps in access, with AI expected to accelerate markets like traditional, complementary, and integrative medicine (TCIM) to nearly $600 billion. Sources of Big Data in Healthcare Big data in healthcare draws from diverse sources, creating a rich ecosystem...