A Large-Scale Monitoring System Using Big Data Analytics In It Industries

Authors

  • Pallavi Baruah Guham  Department of Computer Science, University of Science and Technology, Meghalaya, India
  • Dr. Bhairab Sarma  Department of Computer Science, University of Science and Technology, Meghalaya, India

Keywords:

Big Data, ETL, PANDAS

Abstract

This research paper is based on modelling technique and building a prediction model using Python programming language PANDA to predict data set on large-scale monitoring system using Big Data Analytics in IT Industries. In this research paper, the researcher developed a programming modelling technique which would be identify the customer behaviours patterns using large scale of data. The programming language Python to perform the full life-cycle of any data set. It includes reading, analysing, visualizing and finally making predictions. The Researcher focused on the modelling techniques how attributes / data of applicants or customers are providing a significant role to make a specific decision or generate a new information about their candidatures towards predictions on specific real life problems.

References

  1. Laney, D. (2001). 3D Data Management: Controlling Data Volume, Velocity and Variety. Stamford, CT: META Group.
  2. Jun Liu and Feng Liu (2014),' Monitoring and analyzing big traffic data of a large-scale cellular network with Hadoop', Published in: IEEE Network (Volume: 28, Issue: 4, July-August 2014) Page(s): 32 - 39 Date of Publication: 24 July 2014 Print ISSN: 0890-8044.
  3. Pedro Domingo (2018),' A Few Useful Things to Know about Machine Learning', Department of Computer Science and Engineering University of Washington Seattle, WA 98195-2350, U.S.A.
  4. Nada Elgendy and Ahmed Elragal(2014),' Big Data Analytics: A Literature Review Paper', Conference Paper in Lecture Notes in Computer Science • August 2014, P. Perner (Ed.): ICDM 2014, LNAI 8557, pp. 214–227, 2014. © Springer International Publishing Switzerland 2014.
  5. E. F. CODD (1970),' A Relational Model of Data for Large Shared Data Banks', Information Retrieval, Volume 13 / Number 6 / June, 1970, ACM.
  6. Rajeev Gupta and Himanshu Gupt (2012),' Cloud Computing and Big Data Analytics: What Is New from Databases Perspective?', BDA 2012, LNCS 7678, pp. 42–61, 2012. © Springer-Verlag Berlin Heidelberg 2012
  7. K. Leahy, K. Bruton and D. T. J. O'Sulliva (2015),'An industrial big data pipeline for data?driven analytics maintenance applications in large?scale smart manufacturing facilities', Journal of Big Data, Springer, O'Donovan et al. Journal of Big Data (2015) 2:25
  8. CliffEngle and Antonio Lupher(2012),' Shark: Fast Data Analysis Using Coarse-grained Distributed Memory', SIGMOD'12,May20-24,2012,Scottsdale,Arizona,USA. Copyright2012ACM978-1-4503-1247-9/12/05.
  9. Badrish Chandramouli and Jonathan Goldstein (2013),' Scalable Progressive Analytics on Big Data in the Cloud', August 26th - 30th 2013, Riva del Garda, Trento, Italy. Proceedings of the VLDB Endowment, Vol. 6, No. 14 Copyright 2013 VLDB Endowment 2150-8097/13/14.
  10. D. P. Acharjya and Kauser Ahmed P (2016),' A Survey on Big Data Analytics: Challenges, Open Research Issues and Tool', (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 2, 2016
  11. Matei Zaharia and Mosharaf Chowdhury (2018),' Spark: Cluster Computing with Working Sets', University of California, Berkeley.
  12. G. Sabarmathi and Dr. R. Chinnaiyan (2016),' Big Data Analytics Research Opportunities and Challenges- A Review', International Journal of Advanced Research in Computer Science and Software Engineering, Volume 6, Issue 10, October 2016, ISSN: 2277 128X
  13. Arian Bar and Alessandro Finamore (2014),' Large-scale network traffic monitoring with DB-Stream, a system for rolling big data analyses, published in: 2014 IEEE International Conference on Big Data (Big Data).

International Journal of Scientific Research in Science and Technology

Downloads

Published

2018-07-30

Issue

Volume 4, Issue 9, July-August-2018

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Pallavi Baruah Guham, Dr. Bhairab Sarma, " A Large-Scale Monitoring System Using Big Data Analytics In It Industries, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 9, pp.227-234, July-August-2018.