International Journal of Advanced Computing and Communication Systems

Effective Implementation of Data Segregation & Extraction Using Big Data in E – Health Insurance as a Service

MANOJ KUMAR K, TEJASREE S, Department of Computer Science & Engineering, Sri Venkateswara College of Engineering (SVCE), Tirupati, Andhra Pradesh 517507, India.

SWARNALATHA S, Department of Information Technology, Sri Venkateswara College of Engineering (SVCE), Tirupati, Andhra Pradesh 517507, India.

International Journal of Advanced Computing and Communication Systems

ISSN (Online) : 2347 - 9299

ISSN (Print) : 2347 - 9280

Received On :

Revised On :

Accepted On :

Published On :

Volume 04, Issue 03

Page No : 015-019

Abstract

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.

Keywords

Big data; Data Extraction; segregation; E- health insurance; privacy.

Cite this Article

MANOJ KUMAR K, TEJASREE S and SWARNALATHA S, “Effective Implementation of Data Segregation & Extraction Using Big Data in E – Health Insurance as a Service, ”International Journal of Advanced Computing and Communication Systems, pp. 015-019, November, 2017.

Copyright

© 2017 MANOJ KUMAR K, TEJASREE S and SWARNALATHA S. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.