Vol. 1 No. 1 (2021): African Journal of Artificial Intelligence and Sustainable Development
Articles

Leveraging Cloud Object Storage Mechanisms for Analyzing Massive Datasets

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  • Sarbaree Mishra
Sarbaree Mishra
Program Manager at Molina Healthcare Inc., USA
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Published 12-01-2021

Keywords

  • Cloud object storage,
  • big data analytics,
  • scalability
Creative Commons License

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

How to Cite

[1]
Sarbaree Mishra, “Leveraging Cloud Object Storage Mechanisms for Analyzing Massive Datasets”, African J. of Artificial Int. and Sust. Dev., vol. 1, no. 1, pp. 286–306, Jan. 2021, Accessed: Dec. 18, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/217

Abstract

Cloud object storage has become a cornerstone for managing and analyzing large datasets, offering an efficient and flexible solution for organizations to store and process unstructured and structured data. With the exponential growth of data across various industries, traditional data storage solutions often need help to keep up with the sheer volume and variety of information. With its scalability, durability, and cost-effectiveness, cloud object storage addresses these challenges by providing a centralized platform where businesses can store vast amounts of data and access it seamlessly. This article explores how cloud object storage when paired with modern data analytics tools, enables organizations to unlock valuable insights from massive datasets. The architecture behind cloud object storage is designed to handle high-volume data efficiently while offering flexible access and robust security features. In big data analytics, cloud object storage plays a pivotal role by facilitating data processing at scale & supporting advanced analytics techniques like machine learning and artificial intelligence. Using data lakes and distributed computing frameworks, cloud object storage ensures that large datasets are accessible for real-time analysis, driving faster & more informed decision-making. The article also delves into performance optimization strategies for cloud object storage, such as data tiering and caching, which improve access speed and reduce costs. It also highlights several use cases from industries like finance, healthcare, and e-commerce, demonstrating how organizations leverage cloud object storage to gain competitive advantages. By capitalizing on cloud storage's flexibility, businesses can overcome traditional storage limitations & explore new avenues for innovation and growth. In summary, cloud object storage simplifies the management of massive datasets & enables organizations to harness the power of data-driven decision-making in an ever-evolving digital landscape.

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