Book 978-93-91303-31-0 1st Dr. G. UMA DEVI Dr. G. UMA DEVI 978-93-91303-31-0 9789391303310 Jupiter Publications Consortium Prof. S. MageshChennai, India 10022022 ... ... ...

Big Data Analytics with Hadoop


Name of the Book: Big Data Analytics with Hadoop


Author(s) : Dr. G. UMA DEVI



The phrase “big data” has gained popularity to refer to an exciting new collection of tools and approaches for developing contemporary, data-driven applications that revolutionise the way the world computes. To the dismay of statisticians, this ubiquitous word seems to be widely utilised to include applying well-known statistical methods to big datasets for predictive purposes. Although the term “big data” has become a catchphrase, the reality is that current, distributed processing methods enable studies of datasets far more significant than those previously analysed, with astonishing results. However, distributed computing alone does not imply data science. The combination of constantly growing datasets created by the Internet and the insight that these data sets may power prediction models has resulted in a new economic paradigm known as data products. Stunning data modelling accomplishments across vast, diverse datasets. Hadoop has developed from a cluster computing abstraction to a big data operating system by offering a framework for distributed data storage and parallel processing. Spark expanded on these concepts and simplified cluster computing for data scientists. However, data scientists and analysts unfamiliar with distributed computing may believe that these technologies are designed for programmers rather than analysts. This is because paradigm changes in handling and computing data in a parallel rather than sequential approach are required. This textbook is designed to help Engineering, and Technological Undergraduates comprehend the principles, methods, and procedures involved in big data analytics with Hadoop and serve as a springboard for further exploring subject areas.

Keywords:Big data, Hadoop



  1. Agneeswaran, V. S. (2014). Big data analytics beyond hadoop: real-time applications with storm, spark, and more hadoop alternatives. FT Press.
  2. Anuradha, J. (2015). A brief introduction on Big Data 5Vs characteristics and Hadoop technology. Procedia computer science48, 319-324.
  3. Augustine, D. P. (2014). Leveraging big data analytics and Hadoop in developing India’s healthcare services. International Journal of Computer Applications89(16), 44-50.
  4. Azeroual, O., & Fabre, R. (2021). Processing big data with apache hadoop in the current challenging era of COVID-19. Big Data and Cognitive Computing5(1), 12.
  5. Dhyani, B., & Barthwal, A. (2014). Big data analytics using Hadoop. International Journal of Computer Applications108(12).
  6. Gupta, B., & Jyoti, K. (2014). Big data analytics with hadoop to analyze targeted attacks on enterprise data. (IJCSIT) International Journal of Computer Science and Information Technologies5(3), 3867-3870.
  7. Kousalya, D. R., & Sindhupriya, T. (2017). Review on big data analytics and Hadoop framework. International Journal of Innovations in Scientific and Engineering Research (IJISER), ISSN: 2347-9728 (print)4(3MAR), 101.
  8. Kumar, Y., Sood, K., Kaul, S., & Vasuja, R. (2020). Big data analytics and its benefits in healthcare. In Big data analytics in healthcare(pp. 3-21). Springer, Cham.
  9. Malhotra, J., Sethi, J. K., & Mittal, M. (2021). Analysis of big data using two mapper files in hadoop. International Journal of Security and Privacy in Pervasive Computing (IJSPPC)13(1), 69-77.
  10. Niu, Y., Ying, L., Yang, J., Bao, M., & Sivaparthipan, C. B. (2021). Organizational business intelligence and decision making using big data analytics. Information Processing & Management58(6), 102725.
  11. Priyanka, E. B., Thangavel, S., Meenakshipriya, B., Prabu, D. V., & Sivakumar, N. S. (2021). Big data technologies with computational model computing using hadoop with scheduling challenges. In Deep Learning and Big Data for Intelligent Transportation(pp. 3-19). Springer, Cham.
  12. Rehman, A., Naz, S., & Razzak, I. (2021). Leveraging big data analytics in healthcare enhancement: trends, challenges and opportunities. Multimedia Systems, 1-33.
  13. Wu, W., Lin, W., Hsu, C. H., & He, L. (2018). Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights. Future Generation Computer Systems86, 1351-1367.
  14. Zakir, J., Seymour, T., & Berg, K. (2015). Big Data Analytics. Issues in Information Systems16(2).
  15. Zhang, X., & Wang, Y. (2021). Research on intelligent medical big data system based on Hadoop and blockchain. EURASIP Journal on Wireless Communications and Networking2021(1), 1-21.


ISBN: 978-93-91303-31-0


Volume: 2022


Edition: 1


Pages: 232


Price: INR 375/=


First Published: 10.02.2022


DOI: 9789391303310


Download Sample Pages: Download sample pdf


How to cite this Book: 

Uma Devi, G. (2022). Big Data Analytics with Hadoop (1st ed., pp. 1-232). Jupiter Publications consortium,ISBN:978-93-91303-31-0, DOI: