Research on Various Tools in Big Data
R.S. Karthiga1, Senthil Kumar Janahan2, U.V. Anbazhagu3
1R.S. Karthiga, Department of Electronics and Communication Engineering, VISTAS, Pallavaram, Chennai (TamilNadu), India.
2Senthil Kumar Janahan, Department of Electronics and Communication Engineering, VISTAS, Pallavaram, Chennai (TamilNadu), India.
3U.V. Anbazhagu, Department of Electronics and Communication Engineering, VISTAS, Pallavaram, Chennai (TamilNadu), India.
Manuscript received on 13 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript Published on 26 July 2019 | PP: 1097-1100 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F12280486S419/19©BEIESP | DOI: 10.35940/ijitee.F1228.0486S419
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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: The field big data has wonderful changes in the last few years. Data are collected very massive amount and cheaply through network devices such as mobile, camera, microphone, software logs etc. Information is coming various sources and also the nature of the information is different. It is very difficult to perform with very huge data sets and different nature by using traditional data application software techniques. For many field we need to take out the valuable information from enormous and noisy data sets. In this paper we analyses the characteristics among four different tools and the comparison value is very useful to determine the efficient analytic tool. Based on the value which made user to select the best tool for to advance the performance of big data in a easiest way.
Keywords: Very Difficult to Perform With Very Huge Data Sets and Different Nature by Using Traditional Data Application Software Techniques.
Scope of the Article: Communication