This paper is published in Volume-3, Issue-1, 2017
Area
Big Data
Author
A. Anitha, V. Vaneeswari, R. Abirami
Org/Univ
Bharathidasan University, Tamil Nadu, India
Pub. Date
03 February, 2017
Paper ID
V3I1-1287
Publisher
Keywords
Data Storage, Data Management, Big Data Yield, Characterize (Volume, Variety, Velocity).

Citationsacebook

IEEE
A. Anitha, V. Vaneeswari, R. Abirami. Growth Level of Big Data, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
A. Anitha, V. Vaneeswari, R. Abirami (2017). Growth Level of Big Data. International Journal of Advance Research, Ideas and Innovations in Technology, 3(1) www.IJARIIT.com.

MLA
A. Anitha, V. Vaneeswari, R. Abirami. "Growth Level of Big Data." International Journal of Advance Research, Ideas and Innovations in Technology 3.1 (2017). www.IJARIIT.com.

Abstract

Big data’ is similar to ‘Small-data’, but big data analysis. Big data is, without the doubt, the hot topic nowadays, moreover because the development of new technology makes it possible to analyze all available ever-growing data which easily amasses terabytes of Information. The big data used in 5 billion mobile phones on 2010. There are 30 billion pieces of content shared on Facebook each month is a 40% projected growth in global data generated per year vs. 5% growth in global IT spending. There are 235 terabytes of data collected by the US Library of Congress in April 2011.It is 15 out of 17 major business sectors in the United States have more data stored per company that the US Library of Congress. Then 50 billion devices will be connected by 2020.Every day it seems that a new technique or application is introduced that pushes the edges of the speed-size envelope even further. It boasts scan speeds of 33 million rows/second/core and ingest speeds of 10 thousand records/second/node. The events leading to the discovery and resolution of the scandal point to the promises and challenges of data management for multiparty, multidimensional, international systems. Billions of individual pieces of data are amassed each day, from sources including supplier data, delivery slips, restaurant locations, employment records, DNA 22 records, data from Interpol’s database of international criminals, and also customer complaints and user-generated content such as location check-ins, messages, photos and videos on social media sites. It has used for three different characterize (volume, variety, velocity). Most are keenly aware that Big Data is at the heart of nearly every digital transformation taking place today.