An Overview of Milestones of Big Data Analytics in Clinical and Medical Analysis
Manu M R1, B Balamurugan2

1Manu M R*, Research Scholar, School of Computing Science and Engineering, Galgotias University, Greater Noida (U.P), India.
2Dr. B Balamurugan, Associate Professor, School of Computing Science and Engineering, Galgotias University, Greater Noida (U.P), India

Manuscript received on June 23, 2021. | Revised Manuscript received on June 23, 2021. | Manuscript published on June 30, 2021. | PP: 416-421 | Volume-10 Issue-5, June 2021. | Retrieval Number: 100.1/ijeat.E28990610521 | DOI: 10.35940/ijeat.E2899.0610521
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Abstract: The technological advancements make changes during availability of knowledge in a huge way. As the volume of data is increasing exponentially, there is a need for better management of data to research and industry. This data, referred to as Big Data, is now employed by various organizations to extract valuable information which may reanalyzed computationally to reveal patterns, trends and associations revealing the human interaction and behavior for making various industrial decisions But the data must be optimized, integrated, secured and visualized to make any effective decision. Analyzing of the large volume of data is not beneficial always unless it is analyzed properly. The existing techniques are insufficient to analyze the large Data and identify the frequent services accessed by the cloud users. Various services can be integrated to provide a better environment to work in emergency cases pretty earlier. Using these services, people become widely vulnerable to exposure. The data is large and provides an insight in to future predictions, which could definitely prevent maximum medical cases from happening. But without big data analytics techniques and therefore the Hadoop cluster, this data remains useless. Through this paper, we’ll explain how real time data may be useful to research and predict severe 
Keywords: Big Data, Medical Big Data mining, EHR, EMR, Hadoop, Hbase, Mapreduce, HDFS, Hive, Cassandra 
Scope of the Article: Data mining