Published March 30, 2021 | Version CC BY-NC-ND 4.0
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A Survey on Some Big Data Applications Tools and Technologies

  • 1. Department of Computer Science & Engineering, Sri Padmavathi Mahila Viswa Vidyalayam, Tirupati, India.
  • 2. Department of Computer Science & Engineering , Sri Padmavathi Mahila Viswa Vidyalayam, Tirupati, India.

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  • 1. Department of Computer Science & Engineering, Sri Padmavathi Mahila Viswa Vidyalayam, Tirupati, India.

Description

Abstract: Big Data is a broad area that deals with enormous chunks of data sets. It is a word for enormous data sets having huge volume, more diverse structures of data originating from diverse sources are growing rapidly. Many data being generated because of fast data transmission between devices concerning different sectors like healthcare, science, media, business, entertainment and engineering. Data collection capacity and its storage is big concern. Apache Hadoop software is a store of accessible source programs to store big data and perform analytics and various other operations related to big data. Many organizations base their decisions by extracting knowledge from huge and complex data, because of this prime cause of decision making, Big Data has to be accurately classified and analyzed. In order to overcome the complex challenges encountered by Big Data, various Big Data tools and technologies have developed. Big Data Applications, tools and technologies used to handle it are briefly discussed in this paper.

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Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved.

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References

  • B. Furht and F. Villanustre, "Introduction to big data. In: Big Data Technoogies: Springer International Publishing, Chambers, pp 3–11, 2016.
  • A. McAfee, E. Brynjolfsson, "Big Data: The Management Revolution," Harvard Business Review, pp.60–68, 2012.
  • Rajaraman, "Big data analytics," Resonance vol.21, pp.695–716, 2016.
  • Kune, P.K. Konugurthi, P.K. Agarwal, A. Chillarige, R. Buyya, "The anatomy of big data computing," Software: Practice and Experience 46(1), pp.79–105, 2016.
  • C.K. Emani, N. Cullot, C. Nicolle, "Understandable big data: a survey," Computer Science Review, vol.17, pp.70–81, 2015.
  • Gandomi, M. Haider, "Beyond the hype: Big data concepts, methods, and analytics," IJIM, vol.35, pp.137–144, 2015.
  • Iqbal, F. Doctor, B. More, S. Mahmud, U. Yousuf, "Big Data Analytics: Computational Intelligence Techniques and Application areas,' IJIM, 2016.
  • https://blog.microfocus.com/how-much-data-is-created-on-the-interne t-each-day/
  • Shilpa, M. Kaur, "International Journal of Advanced Research in Computer Science and Software Engineering," vol.3(10), October, pp. 991-995, 2013.
  • Sagiroglu, D. Sinanc, "Big Data: A Review," pp.20-24, May 2013.
  • N. Mangla, R.K. Khola, "Application Based Route Optimization," IOSR Journal of Engineering, vo.2(8), pp.78-82, 2012.
  • https://www.edureka.co/blog/big-data-applications-revolutionizing-va rious-domains
  • https://www.simplilearn.com/how-big-data-powering-internet-of-thin gs-iot-revolution-article
  • https://mapr.com/products/apache-hadoop/
  • Mehta and N. Mangla, "A survey paper on Big Data Analytics using Map Reduce and Hive on Hadoop Framework," IJRAET Volume.4, Issue 2, NCRISTM-2016.
  • Maheshwari, "Big Data," McGraw Hill Education India private limited, second edition.
  • J. Wang, W. Liu, S.kumar and S. Chang, "Learning to Hash for indexing Big Data A survey," arXiv:1509.05472v1 [cs.LG]
  • https://www.qubole.com/products/qubole-data-service/apache-spark-s ervice/
  • M. Israd, M. Budiu, Y. Yu, A. Birrell, D. Fitterly, "Dryad: Distributed Data-parallel Programs from Sequential Building Blocks," Proc. of 2007 Eurosys conf.
  • Gupta, "Learning Apache Mahout Classification," Packt publication, UK, 2015.
  • M. Chen, S. Mao, Y. Liu, "Big Data: A Survey," Springer Science Business Media New York, Mobile Network Applications pp.171-209, 2014.
  • Chambers, J.: Bell Laboratories: What is R? The R Foundation. http://www.r-project.org/. Accessed 5 Aug 2018

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ISSN: 2277-3878 (Online)
https://portal.issn.org/resource/ISSN/2277-3878
Retrieval Number: 100.1/ijrte.F5575039621
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