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Review Article Open Access December 29, 2019

Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making

Ravi Kumar Vankayalapati 1 and Rama Chandra Rao Nampalli 2
1
Cloud AI ML Engineer, Equinix, Dallas, USA
2
Solution Architect, Denver RTD, Parker, CO-80134, USA
Publihed in: Current Research in Public Health (Volume 1, Issue 1, 2021)
Page(s): 1-12
DOI: 10.31586/jaibd.2019.1228
Received
October 19, 2019
Revised
November 28, 2019
Accepted
December 22, 2019
Published
December 29, 2019
Keywords
Explainable Analytics; Multi-Cloud Analytics; Model Explanation; Decision-Making; Visual Analytics; Cloud Brokering; Decision-making; Digital Services; Intelligent cloud Services; Multi-cloud Analytics; Multi-cloud explainability; Multi-cloud Regulation; Ranking Algorithms; Trustful Decisions
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2021. Published by Scientific Publications
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Cite This Article

APA Style
Vankayalapati, R. K. , & Nampalli, R. C. R. (2021). Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making. Current Research in Public Health, 1(1), 1-12. https://doi.org/10.31586/jaibd.2019.1228
ACS Style
Vankayalapati, R. K. ; Nampalli, R. C. R. Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making. Current Research in Public Health 2021 1(1), 1-12. https://doi.org/10.31586/jaibd.2019.1228
Chicago/Turabian Style
Vankayalapati, Ravi Kumar, and Rama Chandra Rao Nampalli. 2021. "Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making". Current Research in Public Health 1, no. 1: 1-12. https://doi.org/10.31586/jaibd.2019.1228
AMA Style
Vankayalapati RK, Nampalli RCR. Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making. Current Research in Public Health. 2021; 1(1):1-12. https://doi.org/10.31586/jaibd.2019.1228 
@Article{crph1228,
AUTHOR = {Vankayalapati, Ravi Kumar and Nampalli, Rama Chandra Rao},
TITLE = {Explainable Analytics in Multi-Cloud Environments: A Framework for Transparent Decision-Making},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {1-12},
URL = {https://www.scipublications.com/journal/index.php/JAIBD/article/view/1228},
ISSN = {2831-5162},
DOI = {10.31586/jaibd.2019.1228},
ABSTRACT = {The multitude of services and resources available in multi-cloud environments has increased the importance of analytics applications in cloud brokering. These applications can orchestrate services and resources that reside in different domains and require inputs that a single cloud provider could not easily acquire. Yet, despite their distinct characteristics, multi-cloud analytics users have no voice in the ranking of the services in brokerage marketplaces. In this chapter, we introduce the concept and propose the implementation of explainable analytics to increase transparency and user satisfaction in multi-cloud environments. The criteria that we have identified and measured in order to summarize them in explainable results allow cloud users to acquire an understanding of the ranking rules, a crucial requirement in trustful decision-making. Our proposal accounts for a set of regulations for intelligent systems and targets their specific adaptation and use in multi-cloud environments.},
}
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