Background: The rapid growth of digital healthcare systems, electronic health records, genomic databases, wearable technologies, and medical imaging has generated unprecedented volumes of healthcare data. Big Data Analytics (BDA) has emerged as a transformative approach for extracting meaningful insights from these complex datasets to improve healthcare research, clinical decision-making, and patient outcomes. Objective: This study examines the role of Big Data Analytics in healthcare research, explores its applications, benefits, challenges, and future opportunities, and evaluates its impact on evidence-based medicine and healthcare innovation. Methods: A narrative review was conducted using peer-reviewed literature published between 2018 and 2025. Databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar were searched. Studies related to healthcare analytics, artificial intelligence, predictive modeling, precision medicine, and population health management were included. Results: Big Data Analytics has significantly improved disease prediction, clinical decision support, precision medicine, epidemiological surveillance, drug discovery, and healthcare management. Key benefits include improved research efficiency, enhanced predictive capabilities, and personalized treatment approaches. Challenges include data privacy concerns, interoperability issues, data quality problems, and ethical considerations. Conclusion: Big Data Analytics is revolutionizing healthcare research by enabling advanced data-driven insights and supporting evidence-based clinical practice. Continued investment in data infrastructure, analytics expertise, and regulatory frameworks is essential for maximizing its potential in modern healthcare systems.