Technicalities and Tools for Big Data Analysis

Authors

  • Partha Ghosh
  • Bijoy Kumar Mandal

DOI:

https://doi.org/10.37591/ctit.v12i2.942

Abstract

Before becoming relevant knowledge and information that can assist management in making decisions, data has no purpose. Numerous top-notch big data applications are available to help with this. In this study we discuss about the mostly used open source tools and techniques used for analysing big data. People started to understand how much data users were producing through Facebook, YouTube, and other online services around 2005. Hadoop, an open-source platform created primarily to store and analyse enormous data collections, was introduced in the same year. As the field of Big Data analytics continues to evolve, we can expect to see even more amazing and transformative applications of this technology in the years to come. Since then, there has been a tremendous increase in the volume of big data.

References

N. Pavithra. and C. M. Manasa., "Big Data Analytics Tools: A Comparative Study &; 2021 IEEE International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), pp. 1-6, 2021,doi: 10.1109/CSITSS54238.2021.9683711.

A. Jaiswal, V. K. Dwivedi and O. P. Yadav;Big Data and its Analyzing Tools: A Perspective", 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), pp. 560-565, 2020.

S. Havre, B. Hetzler, and L. Nowell. Themeriver: Visualizing theme changes over time. In Proc. IEEE Symposium on Information Visualization, pages 115–123, 2000.

Herodotou, H., Lim, H., Luo, G., Borisov, N., Dong, L., Cetin, F.B., and Babu, S. Starfish: A Self-Tuning System for Big Data Analytics. Proc. of CIDIR, 2011.

H J Watson, Tutorial: Big data analytics: Concepts, technologies, and applications, Communication of the Association for Information Systems, Vol.34, Article 65, pp.124–168, 2014

Antony, S., Liu, H., and Murthy, R. Hive – A Petabyte Scale Data Warehouse Using Hadoop. Proc. of ICDE, 2010.

J. Dittrich, J.-A. Quian´e-Ruiz, A. Jindal, Y. Kargin, V. Setty, and J. Schad. Hadoop++: Making a Yellow Elephant Run Like a Cheetah. PVLDB, Vol. 3, No. 1, 2010.

Ramesh Sharda and DursunDelen. Predicting box-office success of motion pictures with neural networks. Expert Systems with Applications, vol 30, pp 243–254, 2006.

Asur, S., Huberman, B.A.: Predicting the Future with Social Media. In: ACM International Conference on Web Intelligence and Intelligent Agent Technology, vol. 1, pp. 492-499, 2010

Shenoy, S., Gorinevsky, D., Predictive analytics for extreme events in big data. In: Proceedings of IEEE International Conference on Big Data Computing Service and Applications, pp. 184–193, 2015.

Verde, R., Irpino, A., Balzanella, A., 2016. Dimension reduction techniques for distributional symbolic data. IEEE Trans. Cybern. Vol. 46, No. 2, pp. 344–355, 2016.

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Published

2022-10-31

Issue

Vol. 12 No. 2 (2022)

Section

Review Articles

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