Diabetic data analysis in healthcare using Hadoop architecture over big data

Owing to the increasing developments in this digitised era, it is
necessary to move from paper health records to digital by handling the large
volume of healthcare data for analysis, and using them for efficient treatment
will be a crucial issue. Diabetes Mellitus (DM) is one of the Non-
Communicable Diseases (NCD). It is a major health hazard in developing
countries and associated with long-term complications and numerous health
disorders. The main idea of this project is to integrate massive unstructured
diabetic data from various sources which need to be normalised into a proper
scale to get optimised solution for medicinal field using Hadoop. Although
the traditional database management systems can handle data effectively,
processing the high volume of unstructured data at a reasonable time becomes
very challenging. This paper uses the predictive analysis algorithm in the
Hadoop/MapReduce environment to predict the DM complexities and the type
of treatment to be adopted. Based on the analysis, this system provides an
efficient way to cure patients with better outcomes.