Open AccessAn Analytical Approach to Big Data Issues in the Health Care Sector Using R Model & Hadoop
Author(s) -
Qusay Abdullah Abed
Publication year - 2022
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v19i1/web19149
Subject(s) - big data , computer science , health care , raw data , data science , process (computing) , service (business) , constructive , adaptation (eye) , process management , data mining , knowledge management , business , marketing , physics , optics , economics , programming language , economic growth , operating system
Big data is a term used to depict the availability and exponential growth of data. The data may be structured or unstructured. It is an all-encompassing expression for any assortment of dataset so complex and large that makes it hard to process by use of traditional data processing applications or on-hand data management tools. Despite of the role of Big Data in healthcare adaptation service there is a concerning of how to analysis this data in efficient and significant way. This problem has negatively affected the healthcare management system from the end user level that represented by patient registration to the clink records. To overcome these issues, we have adopted Hadoop to remedy this current situation, and then we add R model for Map Reduce and adopt R Map Reduce for analytical health care records, and raw data at clink. Additionally, a description of other capabilities has been given to facilitate practical application of Big Data services in the healthcare. This article also reports about the designing of Big Data Healthcare Service architecture, which enhances the management of data analysis operations capabilities, regulatory compliance and constructive Healthcare usages.