Abstract— Due to continuous growth of information systems to store business data and advent of new areas like mobile computing, users now need to use the enterprise applications through tablets, Smartphone, iPhone, laptops, and desktop computers. Effective decision making can be achieved with efficient information system. With the introduction of Business Intelligence tools organizations can now analyze the raw data and perform various activities like data mining, online analytical processing (OLAP), querying and reporting. Business Intelligence technology will help the managers to make better informed decisions. In order to perform data driven decision making business analytics practices are adopted. Cloud computing in recent days has gained a lot of prominence to store and process the business data. Organizations use cloud storage to manage data as they face challenges in local storage. But cloud also possesses certain challenges due to which organizations at large still find difficult to move to the cloud. Cloud computing can also be used to store and process big data. As Big data need to be analyzed for attaining maximum business value a new data model need to be proposed which have the properties those differs from traditional data model. In this paper we discuss that various challenges faced by organizations to move to cloud. We also propose that how the challenges can be overcome by the organizations so that cloud will be a promising architecture for better information management. Data model for Big data is also proposed in this paper.

Index Terms—business intelligence, big data, cloud computing, data mining, OLAP, Information management

Cite: Suryakanthi Tangirala, "Efficient Big Data Analytics and Management through the Usage of Cloud Architecture," Vol. 7, No. 4, pp. 302-307, November, 2016. doi: 10.12720/jait.7.4.302-307