Processing and Analyzing Healthcare Big Data on Cloud Computing Environment by Implementing Hadoop Cluster

In today's world, due to technological advancements, the amount of data that is getting generated is growing rapidly. Enterprises worldwide will need to perform data analytics with these huge data datasets to make business decisions and stay competitive. Storage of data sets and performing data analytics was traditionally accomplished using RDBMS (Relational Database Management System). However, RDBMS would be inefficient and time consuming when performing data analytics on huge data sets. A cloud based big data analytic platform is the best way to analyze the structured and unstructured data generated from healthcare management systems. Hadoop came into existence recently and overcomes the limitations of existing RDBMS by providing simplified tools for efficient data storage and faster processing times for data analytics. The purpose of this work is to perform data analytics on a health care data set using Hadoop functionalities. A health care data set comprising of 1.5 million patient records is considered for the data analysis. Different use cases as to be considered and will perform analytics using MapReduce, Hive and Pig functionalities of Hadoop.