Download PDFOpen PDF in browserCurrent version

Cloud Computing Solutions for Artificial Intelligence’s Data Quality and Security Challenges

EasyChair Preprint 13653, version 5

Versions: 123456789101112history
11 pagesDate: July 26, 2024

Abstract

The rapid increase in data volume and complexity presents significant challenges in processing, storing, and analyzing Big Data. Cloud computing has emerged as a critical tool to address these issues. This paper offers an in-depth examination of cloud computing solutions tailored to Big Data problems, focusing on technologies and services that enable scalable, cost-effective, and secure data management and analytics. Building on the findings from "Fortifying the Global Data Fortress: A Multidimensional Examination of Cyber Security Indexes and Data Protection Measures Across 193 Nations," the discussion extends to the role of cloud computing in enhancing data security and fortifying global data protection measures. The study integrates insights from global cybersecurity trends to demonstrate how cloud solutions can mitigate cyber threats and promote a robust global digital ecosystem. Through real-world case studies and practical examples, this paper serves as a guide for businesses and researchers looking to leverage cloud computing to overcome Big Data challenges and bolster cybersecurity on an international scale.

Keyphrases: Artificial Intelligence, Big Data, Cloud Computing, Cloud Providers, Cloud Services, Data Analytics, Data Quality, Data Security, Innovation, Scalability, Security, case studies, competitiveness, cost efficiency, data management, data processing, data storage, data-driven decision making, machine learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:13653,
  author    = {John Kelly and William Smith},
  title     = {Cloud Computing Solutions for Artificial Intelligence’s Data Quality and Security Challenges},
  howpublished = {EasyChair Preprint 13653},
  year      = {EasyChair, 2024}}
Download PDFOpen PDF in browserCurrent version