The concept of big data in healthcare has been introduced previously. It refers to the massive amounts of data generated by the healthcare industry that are too large and difficult to manage with typical database management systems. Big data analytics can help analyze and make sense of this data, improving healthcare quality, reducing costs, and facilitating timely decision-making. Most of the review focuses on the sources of big data and the benefits of big data in healthcare but rarely on big data challenges and strategies to overcome those challenges. The aim and objective of this review are to provide an overview of the characteristics of big data, its potential benefits and challenges, and its impact on the future of medicine. It also explores the challenges associated with big data in healthcare and strategies to overcome those challenges in healthcare big data which include data quality assessment, data governance and privacy, cloud computing, data analytics, data sharing and collaboration, interoperability, patient engagement, data visualization, data security and protection, and continuous improvement. Interoperability can help manage and analyze data, and patient engagement can increase the volume and diversity of data available for analysis. Data visualization techniques can help healthcare organizations better understand and communicate insights from big data. As the quantity of healthcare data continues to increase, the opportunity to utilize this data to enhance healthcare delivery and results will increase. Ultimately, big data in healthcare has the potential to lead to better patient outcomes, cost reduction, faster medical research, improved population health, and personalized medicine.

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