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The Challenges of Business Intelligence in Cloud Computing


Affiliations
1 PG and Research Department of Computer Science and Application, Quaid-E-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, India
 

Background/Objectives: Cloud technology is one of the trending acquisitions by IT industry and cloud organizations. Though it comes with numerous challenges and cost barriers, it is still considered to be an important source of commercial analytics. Methods/Statistical Analysis: Cloud combines itself with facets available in the organizations. Necessarily it doesn't seek for technical domains but matches with all available resources. Business Intelligences is a wonder source that enhances itself with cloud terminology and technical nuances of cloud resources. Response time and aspects of business intelligence solutions goes hand in hand. This paper gives a clear understanding and deep insights on mathematical indicators of Business Intelligence (BI) and its encounters with cloud lexicons. Findings: This study analyses the crucial challenges that accompanies cloud technology when utilized with business intelligence. Major contribution lies around the crucial uncertainties that overrule the opportunities in cloud computing. Mathematical analyses like return on investment and payback value methods which are used to determine the economic hand-outs and proportions towards the obtainable tenets are also deliberated in this work. Agility is measured in terms of the potential users that bypass cloud resources through business intelligence. The study also encompasses various Business intelligence chauffeurs. Applications/Improvements: The concept of BI can be well handled through cloud tools like CloudSim, CloudAnalyst and Aneka using different models of cloud. The results can be improvised with the capability of BI methods.

Keywords

Business Intelligence (BI), Capital Expenses, Response Time, Return on Investment, Service Allocator.
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  • The Challenges of Business Intelligence in Cloud Computing

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Authors

Ananthi Sheshasaayee
PG and Research Department of Computer Science and Application, Quaid-E-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, India
T. A. Swetha Margaret
PG and Research Department of Computer Science and Application, Quaid-E-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, India

Abstract


Background/Objectives: Cloud technology is one of the trending acquisitions by IT industry and cloud organizations. Though it comes with numerous challenges and cost barriers, it is still considered to be an important source of commercial analytics. Methods/Statistical Analysis: Cloud combines itself with facets available in the organizations. Necessarily it doesn't seek for technical domains but matches with all available resources. Business Intelligences is a wonder source that enhances itself with cloud terminology and technical nuances of cloud resources. Response time and aspects of business intelligence solutions goes hand in hand. This paper gives a clear understanding and deep insights on mathematical indicators of Business Intelligence (BI) and its encounters with cloud lexicons. Findings: This study analyses the crucial challenges that accompanies cloud technology when utilized with business intelligence. Major contribution lies around the crucial uncertainties that overrule the opportunities in cloud computing. Mathematical analyses like return on investment and payback value methods which are used to determine the economic hand-outs and proportions towards the obtainable tenets are also deliberated in this work. Agility is measured in terms of the potential users that bypass cloud resources through business intelligence. The study also encompasses various Business intelligence chauffeurs. Applications/Improvements: The concept of BI can be well handled through cloud tools like CloudSim, CloudAnalyst and Aneka using different models of cloud. The results can be improvised with the capability of BI methods.

Keywords


Business Intelligence (BI), Capital Expenses, Response Time, Return on Investment, Service Allocator.



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i36%2F130060