Comprehensive Survey of Big Data Mining Approaches in Cloud Systems

Authors

  • Zainab Salih Ageed Translation Dept., Nawroz University, Duhok, Iraq
  • Subhi R. M. Zeebaree Culture Center, Duhok Polytechnic University, Duhok, Iraq
  • Mohammed Mohammed Sadeeq Quality Assurance Duhok Polytechnic University Duhok, Iraq
  • Shakir Fattah Kak Dept. Information Technology Duhok Polytechnic University Duhok -Iraq
  • Hazha Saeed Yahia Information Technology Dept. Lebanese French University, Erbil, Iraq
  • Mayyadah R. Mahmood Computer Science Dept University of Zakho Duhok, Iraq
  • Ibrahim Mahmood Ibrahim Information Technology Dept. Duhok Polytechnic University Duhok -Iraq

DOI:

https://doi.org/10.48161/qaj.v1n2a46

Keywords:

Big Data, Data Computing, Big Data Mining, Cloud Computing

Abstract

Cloud computing, data mining, and big online data are discussed in this paper as hybridization possibilities. The method of analyzing and visualizing vast volumes of data is known as the visualization of data mining. The effect of computing conventions and algorithms on detailed storage and data communication requirements has been studied. When researching these approaches to data storage in big data, the data analytical viewpoint is often explored. These terminology and aspects have been used to address methodological development as well as problem statements. This will assist in the investigation of computational capacity as well as new knowledge in this area. The patterns of using big data were compared in about fifteen articles. In this paper, we research Big Data Mining Approaches in Cloud Systems and address cloud-compatible problems and computing techniques to promote Big Data Mining in Cloud Systems.

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References

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Published

2021-04-14

How to Cite

Salih Ageed, Z., R. M. Zeebaree, S. . ., Mohammed Sadeeq, M., Fattah Kak, S. ., Saeed Yahia, H. ., R. Mahmood, M., & Mahmood Ibrahim, I. . (2021). Comprehensive Survey of Big Data Mining Approaches in Cloud Systems . Qubahan Academic Journal, 1(2), 29–38. https://doi.org/10.48161/qaj.v1n2a46

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