Big Data Challenges and Analytics Processing Over Medical Data

Nowadays healthcare sector grows tremendously in last few decades. Insight of how we can uncover additional value from the data generated by healthcare and government. Large amount of heterogeneous data is generated by the agencies; this includes patient’s previous medical data, laboratory test values, and current treatment given to patient, doctor’s prescription, and diagnostic reports. However, the complex distributed and highly interdisciplinary nature of medical data has underscored the limitations of traditional data analysis capabilities of data accessing, storage, processing, analyzing, distributing, and sharing.  In this paper we will discuss future trends of data mining that are used for analysis and prediction of big data. And also we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. Here introduce solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data. Then finally data is analyzed using Apache Mahout for faster query access. These issues include Big Data benefits, its applications and opportunities in medical areas and health care. Methods and technology progress about Big Data are presented in this study.