A Review on Big Data Analytics and Its Tools
DOI:
https://doi.org/10.32628/IJSRST52310684Keywords:
Big Data Analytics, Volume, Veracity, Value, Variety, VelocityAbstract
Big data is a term which refers to the huge volume of data and this data is continuously growing with the time. This data is very large and complex which is difficult to store and process by the traditional software or applications. We can say that big data is an updated or upgraded version of traditional data. Big data deals with structured, unstructured data set and can be a mixture of both structured and unstructured data generally called as semi structured data which is enormous and complex to manage.
References
- M. S. Mahmud, J. Z. Huang, S. Salloum, T. Z. Emara and K. Sadatdiynov, "A survey of data partitioning and sampling methods to support big data analysis," in Big Data Mining and Analytics, vol. 3, no. 2, pp. 85-101, June 2020, doi: 10.26599/BDMA.2019.9020015.
- G. Zhai, Y. Yang, H. Wang and S. Du, "Multi-attention fusion modeling for sentiment analysis of educational big data," in Big Data Mining and Analytics, vol. 3, no. 4, pp. 311-319, Dec. 2020, doi: 10.26599/BDMA.2020.9020024.
- S. Singh and N. Singh, "Big Data analytics," 2012 International Conference on Communication, Information & Computing Technology (ICCICT), 2012, pp. 1-4, doi: 10.1109/ICCICT.2012.6398180.
- T. Garg and S. Khullar, "Big Data Analytics: Applications, Challenges & Future Directions," 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2020, pp. 923-928, doi: 10.1109/ICRITO48877.2020.9197797.
- C. Komalavalli and C. Laroiya, "Challenges in Big Data Analytics Techniques: A Survey," 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2019, pp. 223-228, doi: 10.1109/CONFLUENCE.2019.8776932.
- R. Vatrapu, R. R. Mukkamala, A. Hussain and B. Flesch, "Social Set Analysis: A Set Theoretical Approach to Big Data Analytics," in IEEE Access, vol. 4, pp. 2542-2571, 2016, doi: 10.1109/ACCESS.2016.2559584.
- M. Li, H. Wang and J. Li, "Mining conditional functional dependency rules on big data," in Big Data Mining and Analytics, vol. 3, no. 1, pp. 68-84, March 2020,doi:10.26599/BDMA.2019.902009
- Y. He, F. R. Yu, N. Zhao, H. Yin, H. Yao and R. C. Qiu, "Big Data Analytics in Mobile Cellular Networks," in IEEE Access, vol. 4, pp. 1985-1996, 2016, doi:10.1109/ACCESS.2016.2540520.
- De Mauro, A., Greco, M. and Grimaldi, M. (2016), "A formal definition of Big Data based on its essential features", Library Review, Vol. 65 No. 3, pp. 122-135. https://doi.org/10.1108/LR-06-2015-0061.
- W. M. Al-Rahmi et al., "Big Data Adoption and Knowledge Management Sharing: An Empirical Investigation on Their Adoption and Sustainability as a Purpose of Education," in IEEE Access, vol. 7, pp. 47245-47258, 2019, doi: 10.1109/ACCESS.2019.2906668.
- D. P. Acharjya and Kauser Ahmed, “A Survey on Big Data Analytics: Challenges, Open Research Issues and Tools” in (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 2, 2016.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRST

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