A Prediction of Different Technologies for the Development of Unstructured Big Data
Parashiva Murthy B M1, Sumithra Devi K A2
1Parashiva Murthy B M*, Department of CSE, JSS Science and Technology University, Mysuru, India.
2Sumithra Devi K A, Department of CSE, Dayanand Sagar Academy of Technology and Management, Bengaluru, India.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 25, 2019. | Manuscript published on January 10, 2020. | PP: 2589-2595 | Volume-9 Issue-3, January 2020. | Retrieval Number: B6829129219/2020©BEIESP | DOI: 10.35940/ijitee.B6829.019320
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© 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, a huge volume of terabytes of data is generated from digital technologies and modern information systems, namely Internet of Things and cloud computing. The extraction of knowledge for making decisions from the analysis of these massive data, leads to requires a huge effort at multiple levels. Hence, the researchers focused on Big Data Analysis (BDA) for better development. Traditional platforms and data techniques are very less efficient in Big Data (BD) context, which shows the lack of accuracy, performance, scalability and slow responsiveness. Several works are carried out to address the complex BD challenges by developing new technologies and different types of distributions. In this research work, various technologies which are developed for BD are described and the impact of open research issues, challenges and tools for processing the BD are discussed. Then, the impacts on key business performances for BD are evaluated. At last, this work presented the four major technical and managerial challenges, which provides a platform for exploring BD at numerous stages.
Keywords: Big Data Analysis, Cloud Computing, Decision Making, Internet of Things, Massive Data, Scalability.
Scope of the Article: Cloud Computing