International Journal of Computer Engineering and Technology (IJCET)

Source ID:00000005
Volume 9, Issue 6,November 2018, Pages 115-124, Page Count - 10


Manisha Valera (1) Parth Patel (2) Shruti Chettiar (3)

(1) Department of Computer Engineering, INDUS University, Ahmedabad , India.
(2) Department of Computer Engineering, INDUS University, Ahmedabad , India.
(3) Department of Computer Engineering, INDUS University, Ahmedabad , India.

Manuscript ID:- 00000-21088
Access Type : Open Access
Read Full Article


Administration of data and its analysis have been an ineludible part of the world for ages now. With the progression of big data, myriad number of companies that dealt with a large quantum of data gained momentum as major issues regarding management of data had found an optimistic solution. Even the field of analytics got a boost because of the numerous techniques introduced by big data for analysis of enormous quantity of data. Various methodologies introduced by big data for analytics that yield groundbreaking throughputs with high efficiency rates tend to develop complexities which could lead to damage of catastrophic scale. The major causes included security and storage which needed an immediate solution that is reliable and flexible. This gave rise to the concepts of decentralization and distributed system which when combined together engendered a new technology i.e. BlockChain. It is distributed ledger network that helps in making transactions without any centralized entity being needed. BlockChain is a full-proof solution to the problems of big data analytics as it not undergoes operations safely but also takes care of the storage issue. This newly developed technology has been in the light for a while now. BlockChain has found applications in various sectors which include industrial, medical, banking, and educational as well as defense. This paper discusses the concept of big data, its analytics and BlockChain. It elucidates the techniques and technologies involved in big data analytics and blockchain mechanism. It further discusses how Big data has impacted the canonical ways of handling data, the significance of Big data analytics and how the BlockChain Technology could be used similarly to tackle the issues in Big data analytics. The aim of this paper is to encourage further research in incorporating the BlockChain Technology into Big Data Analytics.
Author Keywords
Big data big data analytics Blockchain.
Index Keywords
Inspecting cleaning transforming and modelling big data

ISSN Print: 0976-6367 ISSN Online: 0976-6375
Source Type: Journals Document Type: Journal Article
Publication Language: English DOI: 10.34218/IJCET.09.6.2018.014
Abbreviated Journal Title: IJCET Access Type: Open Access
Publisher Name: IAEME Publication Resource Licence: CC BY-NC
Major Subject:Physical Sciences Subject Area classification: Computer Science
Subject area: General Computer Science Source: SCOPEDATABASE
References (29)
  1. N. Elgendy, A. Elragal
    Big Data Analytics: A Literature Review Paper
    (2014), In the Proceedings of the 14th Industrial Conference, , Russia, Page No 214-227,
  2. X. Wu, X. Zhu, G. Wu, W. Ding
    Data mining with big data
    (2014) Volume 26, Issue 1, Page No 97-107,
  3. Z.M. Bi, D.S. Cochran
    Big data analytics with applications
    (2014) Volume 1, Issue 4, Page No 249-265,
  4. H.J. Watson
    Harnessing Customer Information for Strategic Advantage: Technical Challenges and Business Solutions,USA
  5. Chen, H., Chiang, R. H. L., & Storey, V. C.
    Business Intelligence and Analytics: From Big Data to Big Impact
    (2012) Volume 36, Issue 4, Page No 1165–1188,
  6. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H.
    Big data: The next frontier for innovation, competition, and productivity
    (2011)Page No 1-143,
  7. Picciano, A. G.
    The Evolution of Big Data and Learning Analytics in American Higher Education
    (2012) Volume 16, Issue 3, Page No 9-20,
  8. P. Russom
     TDWI Best Practices Report: Big Data Analytics,

    (2011), The Data Warehouse Institute (TDWI), USA,
  9. Hey, T., Tansley, S., & Tolle, K.
    The fourth paradigm data-intensive scientific discovery

    (2009), Microsoft research,
  10. M.A. Wani, S. Jabin
    Big Data: Issues, Challenges and Techniques in Business Intelligence
    (2015), In the proceedings of 50th Golden Jubilee Annual Convention, , Springer,
  11. Dylan Maltby
    Big Data Analytics
    (2014), University of Austin, Texas
  12. A. Katal, M. Wazid, R H Goudar
    Big Data: Issues, Challenges, Tools and Good Practices
    (2013), Sixth International Conference on Contemporary Computing,, , India, Page No 404-409,
  13. Shivaraj Koti, Shivananda V. Seeri
    A Survey on Big Data Issues and Challenges
    (2017) Volume 19, Issue 2, Page No 75-78,
    Blockchain Technology & Regulatory Investigations 
    (2018)Page No 35-44,
  15. Melanie Swan
    Blockchain: Blueprint for a New Economy 
    (2015), O’Reilly Media,
  16. F. Xavier, M. Zhegu
    Research Handbook on Digital Transformation Edward Elgar
    (2016), UK,
  17. Zibin Zheng, Shaoan Xie
    Blockchain challenges and opportunities: a survey
    (2018) Volume 14, Issue 4,
  18. Nolan Bauerle.
    How does blockchain technology work? Available at:
    [url+= technology-work/, 2018. Accessed Oct 2018].
  19. T.S. Sharma
    How does blockchain use public key cryptography?
  20. How Blockchain Analytics find its way in Data Analysis 
    (May 23 ,2018),
  21. Zheng BK, Zhu LH, Shen M et al
    Scalable and privacy-preserving data sharing based on blockchain
    (2018) Volume 33, Issue 3, Page No 557–567,
  22. Blockchain Data Storage
  23. Here's How You Can Secure Your Data with Blockchain
  24. What is blockchain technology? Why it is believed to change the world?
    (Aug 23 ,2018),
  25. Lee, J., Lapira, E., Bagheri, B., & Kao, Hung-an
    Recent advances and trends in predictive manufacturing systems in big data environment
    (2013) Volume 1, Issue 1, Page No 38-41,
  26. R. Kune, P. K. Konugurthi, A. Agarwal, R.R. Chillarige and R. Buyya
    The anatomy of big data computing
    (2015), John Wiley & Sons, India,
  27. King, I, Lyu, M. R., & Yang, H
    Online learning for big data analytics
    (2013), IEEE Big data,
  28. A. Back, M. Corallo, L. Dashjr, M. Friedenbach, G. Maxwell, A. Miller, A. Poelstra, J. Timón, and P. Wuille
    Enabling Blockchain Innovations with Pegged Sidechains

  29. Francisca Adoma Acheampong
    Big Data, Machine Learning and the BlockChain Technology: An Overview
    (2018) Volume 180, Issue 20,