Big Data Mining : Tools, Technique, Application

Authors

  • Neelakshi Singh  Computer Science, Institute of Technology & Management, Gwalior, Madhya Pradesh, India
  • Kunal Singh Rajput  Computer Science, Institute of Technology & Management, Gwalior, Madhya Pradesh, India
  • Rashmi Pandey  Assistant Professor, Computer Science, Institute of Technology & Management, Gwalior, Madhya Pradesh, India

DOI:

https://doi.org//10.32628/CSEIT239065

Keywords:

Bigdata, Traditional Data, Analysis, Tools, Business Intelligence

Abstract

Beyond the capabilities of traditional applications, big data is a vast dataset of incredible complexity. In the modern environment, it includes enormous, intricate, and voluminous structured, semi-structured, and unstructured data, together with hidden data supplied from various domains and origins. The duties of data extraction, analysis, visualization, sharing, storage, transmission, and retrieval are all included in the issues provided by the management of big data. As a result, it becomes urgently necessary to develop effective and efficient methods for mining big data.

References

  1. Kudyba, S. (2014). Big Data, Mining, and Analytics: Components of Strategic Decision Making. CRC Press.
  2. Elorie Knilans, “The 5 V’s of Big Data”, Avnet Advantage: The Blog, Soulution- Focused Insight for Growth-Minded VARs. http://blogging.avnet.com/ts/advantag e/2014/07/the-5- vs-of-big-data/#comment-474 (Last seen 05–April–2015)
  3. The Four V’s of Big Data – IBM http://www.ibmbigdatahub.com/infogr aphic/four-vs-big- data (last seen 05–April–2015). 4.Feinleib, D. (2014). Doing a Big Data Project. In Big Data Bootcamp (pp. 103- 123).Apress.

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Published

2023-12-30

Issue

Section

Research Articles

How to Cite

[1]
Neelakshi Singh, Kunal Singh Rajput, Rashmi Pandey, " Big Data Mining : Tools, Technique, Application, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 6, pp.77-81, November-December-2023. Available at doi : https://doi.org/10.32628/CSEIT239065