Transformation of Healthcare through Big Data Analytics

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TIME SERIES ANALYSIS: A time series is a sequence of data points consisting of successive measurements made over a time interval. VISUALIZATION: is a method for creating images, diagrams, or animations to relay a message. MASSIVELY PARALLEL-PROCESSING (MPP) DATABASES: involves using a large number of processors to perform operations simultaneously. SEARCH-BASED APPLICATIONS: SBAs use semantic technologies to process and classify unstructured and structured content across multiple databases, and employ technologies for accessing information. DATA MINING: means searching and analyzing large masses of data to discover patterns and develop new information. CLUSTERED FILE SYSTEMS: They provide redundancy, which improves reliability and it does this by sharing on multiple servers. DISTRIBUTED DATABASES: A distributed database system consists of loosely coupled systems that have no common physical components. CLOUD-BASED INFRASTRUCTURE: is an internet-based computing, where shared resources and information are provided to computers and other devices on request HEALTHCARE AND BIG DATA TRANSFORMATION OF HEALTHCARE SECTOR BY BIG DATA [15] The healthcare sector has seen some remarkable transformation from the once chaotic, expensive and substandard services to quality and efficient health care services. Big data and its analytics brought out this change and can be seen the following areas in the health sector Population health: Big data allows physicians study larger populations as well as treatments to improve people 's lives. Preventive care: With big data, it is possible to analyze a patient’s purchases and anticipate potential future health care needs, an instance; a patient who smokes cigarettes has a higher risk for lung related... ... middle of paper ... ... the information is shared with insurance companies, they could raise their rates. Using data from different sources such as a patient medical record which may be accurate and data from external sources which could affect the accuracy of the conclusions and ultimately, lead to wrong prescription. Thus raises a concern about whether we should use the data. CONCLUSION A large amount of data is generated in the healthcare industry from providers, pharmacies and consumers. Challenges are faced in accessing, storing and transforming the data into usable form. Big data has improved the quality of health care and further investment in expert knowledge solutions and infrastructures is needed to advance its use in healthcare although actions of doctors and nurses and the personal connection they have with their patients will always remain vital in providing high-quality care.

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