JOURNAL ARTICLE

Facilitating big-data management in modern business and organizations using cloud computing: a comprehensive study.

  • Published In: Journal of Management & Organization, 2023, v. 29, n. 4. P. 697 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Qi, Wenhao; Sun, Meng; Hosseini, Seyed Reza Aghaseyed 3 of 3

Abstract

Modern digital life has produced big data in modern businesses and organizations. To derive information for decision-making from these enormous data sets, a lot of work is required at several levels. The storage, transmission, processing, mining, and serving of big data create problems for digital domains. Despite several efforts to implement big data in businesses, basic issues with big data remain (particularly big-data management (BDM)). Cloud computing, for example, provides companies with well-suited, cost-effective, and consistent on-demand services for big data and analytics. This paper introduces the modern systems for organizational BDM. This article analyzes the latest research to manage organization-generated data using cloud computing. The findings revealed several benefits in integrating big data and cloud computing, the most notable of which is increased company efficiency and improved international trade. This study also highlighted some hazards in the sophisticated computing environment. Cloud computing has the potential to improve corporate management and accountants' jobs significantly. This article's major contribution is to discuss the demands, advantages, and problems of using big data and cloud computing in contemporary businesses and institutions. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Management & Organization. 2023/07, Vol. 29, Issue 4, p697
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:1833-3672
  • DOI:10.1017/jmo.2022.17
  • Accession Number:172342202
  • Copyright Statement:Copyright of Journal of Management & Organization is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.