Effective Implementation of Data Segregation and Extraction Using Big Data in E-Health Insurance as a Service

Big data is emerging technology now in all areas, i.e. like online purchase, E-healthcare, tweet analysis, and banking sector. Now a day's insurance companies are showing interest towards analysis of their huge datasets consists of patient's and hospital's information. From those data sets they extracting some useful information. Mostly they concentrate on success and failure percentage and feedback given by patients. Patients will be applying the hospital bills along with discharge summary, medical reports to the insurance company. Based on the patient procedure insurance company will decide to approve the claim and suggest for new patients. Here in this paper patients records, reports, symptoms, and feedbacks are analyzed using big data technologies like infinispan and map reduce concepts for data extraction and segregation in E-health insurance. Disclosing of patients' private information has been done using private data encoding algorithm.