Big data analytics in health informatics

Big Data analytics in healthcare is emerging as a promising field and is most trusted technology today that is used to determine significant insights of huge data sets with minimized costs and improved results. Big data is defined as very large volume of high velocity, complex and variable data that needs innovative techniques to enable the data or information capture, storing, dissemination, management and analysis. The data volume of healthcare systems in enormous and is gaining fast momentum with respect to almost every area of research as well as industry. Nonetheless it provide appropriate storage and access platform for the healthcare systems also. Big data encapsulates the data characteristics such as variety, velocity, veracity with respect to healthcare. The conventional analytical techniques focuses on the large amount of (but currently unanalyzed) patient-related health and medical data available to influence more deeper understanding of the results and these could be further extended to the point of healthcare. The strategic methodology is based on the patient informing the data and the physician using it to perform decision making and giving most appropriate treatment to the latter. This paper discusses the Big data relevance, rationale, utilization and benefits with the healthcare perspective. It provides a summary of recent improvements in big data in health informatics and discusses how these will benefit from the integration of different personalized information from a varied range of data gathered by variable sources (structured or unstructured). In future it is predicted that recent advances in big data will help in increasing our knowledge for testing new theories of disease management from diagnosis to prevention.