Big Data Challenges and Solutions in Healthcare: A Survey

The digitization of medical data, field of genomics and use of wearable sensors to monitor patient health are some of the factors that have dramatically increased the growth of Big Data in Health Care/Biomedicine. Big data in healthcare actually refers to electronic health data sets which are large and complex that is very difficult to manage with traditional/conventional data management tools and techniques. Big data analytics in healthcare is cumbersome not just because of its volume but also because of the diversity of data types and the speed at which it is generated and must be managed/analyzed. Rapid progress is to be made for analyzing this data and for gleaning new insights for making better informed decisions. There are unprecedented opportunities to use big data. The Health Care Industry should find methods to properly analyze this Big HealthCare Data generated and stored around the world each seconds in order to discover associations, understand the patterns and trends which will provide significant opportunities for real-time tracking of diseases, predicting disease outbreaks, to improve care, save lives and lower costs. Extraction, integration and analysis of heterogeneous, enormous and complex HealthCare data captured from various Electronic Health Care sources are a major challenge. New methods, applications and tools that are used by Healthcare industries, practitioners and researchers to tackle the big data challenges are discussed in this paper.