Loading

A Big Data Analysis on Distributed File Storage System
C. Yosepu1, C. Mahesh2

1C. Yosepu*, Department of Computer Science and Engineering, Veltech Rangarajan Dr. Sagunthala R&D Institutute of Science and Technology, Chennai, India.
2Dr. C. Mahesh, Department of Information Technology, Veltech Rangarajan Dr. Sagunthala R&D Institutute of Science and Technology, Chennai, India.

Manuscript received on November 13, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 2383-2388 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6427129219/2019©BEIESP | DOI: 10.35940/ijitee.B6427.129219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Nowadays, the digital technologies and information systems (i.e. cloud computing and Internet of Things) generated the vast data in terabytes to extract the knowledge for making a better decision by the end users. However, these massive data require a large effort of researchers at multiple levels to analyze for decision making. To find a better development, researchers concentrated on Big Data Analysis (BDA), but the traditional databases, data techniques and platforms suffers from storage, imbalance data, scalability, insufficient accuracy, slow responsiveness and scalability, which leads to very less efficiency in Big Data (BD) context. Therefore, the main objective of this research is to present a generalized view of complete BD system that consists of various stages and major components of every stage to process the BD. In specific, the data management process describes the NoSQL databases and different Parallel Distributed File Systems (PDFS) and then, the impact of challenges, analyzed for BD with recent developments provides a better understanding that how different tools and technologies apply to solve real-life applications. 
Keywords: Big Data Analysis, Databases, Data Management, Massive Data, Parallel Distributed File Systems, Scalability, Storage..
Scope of the Article: Big Data Analytics