An Efficient Framework for Creating Twitter Mart on a Hybrid Cloud
Imran Khan, S. Kazim Naqvi, Mansaf Alam, M. N. Doja, S. N. A. Rizvi · International Journal of Information Technology and Computer Science · 2017
The contemporary era of technological quest is buzzing with two words -Big Data and Cloud Computing.Digital data is growing rapidly from Gigabytes (GBs), terabytes (TBs) to Petabytes (PBs), and thereby burgeoning data management challenges.Social networking sites like Twitter, Facebook, Google+ etc generate huge data chunks on daily basis.Among them, twitter masks as the largest source of publicly available mammoth data chunks intended for various objectives of research and development.In order to further research in this fast emerging area of managing Big Data, we propose a novel framework for doing analysis on Big Data and show its implementation by creating a "Twitter Mart" which is a compilation of subject specific tweets that address some of the challenges for industries engaged in analyzing subject specific data.In this paper, we adduce algorithms and an holistic model that aids in effective stockpiling and retrieving data in an efficient manner.