The IoT applications consist of millions of smart devices. For every second, a massive amount of data is generated by those IoT devices. This Big data processing is an important criterion to manage the IoT data generation and optimizes the performance of an IoT system. Big data management analyzes the massive IoT data in real-time. Big data management analyzes the available IoT data and only retrieves the significant information from the data. Big data management optimizes the business process. It plays a significant role in maintaining the reports of patients in healthcare applications. Lack of knowledge professionals, security, data increasing problems, big data tool selection, data integration, and lack of massive data understanding are the main challenges of big data management. Some of the examples of big data are medical healthcare, transaction processing systems, smart grids, mobile applications, and customer database maintenance.
   Processing this wealth of data is a daunting task, and it forces us to adopt smart and scalable computational strategies, including machine intelligence, big data analytics, and data classification. The authors can use the Big Data analysis for effective decision making in the healthcare domain using the existing machine learning algorithms with some modifications. The fundamental purpose of this topic is to summarize the role of Big Data analysis in healthcare and provide a comprehensive analysis of the various techniques involved in mining big data.