Data Analyzing with Cloud Computing Including Related Tools and Techniques

Authors

  • Djabeur Mohamed Seifeddine Zekrifa Higher School of Food Science and Agri-Food Industry, Ahmed Hamidouche Av, Oued Smar, Algiers 16200, Algeria
  • Abhishek Sharma Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, Madhya Pradesh, India.
  • Satyam Department of Electronics and Communication Engineering, Mohan Babu University, Tirupati, Andhra Pradesh-517102.
  • Abhijit Janardan Patankar Department of Information Technology, D y Patil College Of Engineering, Akurdi, Pune.
  • Kalyan Devappa Bamane Department of Information Technology, D y Patil College Of Engineering, Akurdi, Pune.

Keywords:

cloud-based analytics, Artificial Intelligence, Deep Learning Technology, Machine Learning

Abstract

The arrival of the digital era has led to an increase in a variety of data kinds, which continues to grow with each passing day. In point of fact, it is anticipated that by the year 2016, the cloud will store fifty percent of all data. The complexity of this data necessitates its storage, processing, and examination in order to provide information that may be put to use by organizations. The needs of big data analytics in terms of storage and computational power make cloud computing an ideal platform for carrying out the aforementioned objectives. Because of this, cloud-based analytics is now a study subject that may be pursued. However, before actual implementations of this synergistic model can be deployed in a widespread manner, a number of concerns need to be resolved, and dangers need to be reduced. This article investigates the current research in this area of study, as well as its obstacles, unanswered questions, and potential future research directions.

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References

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Published

12.07.2023

How to Cite

Zekrifa, D. M. S. ., Sharma, A. ., Satyam, Patankar, A. J. ., & Bamane, K. D. . (2023). Data Analyzing with Cloud Computing Including Related Tools and Techniques. International Journal of Intelligent Systems and Applications in Engineering, 11(9s), 233–238. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/3112

Issue

Vol. 11 No. 9s (2023)

Section

Research Article

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