A Comprehensive Study on the Big Data Adaptation and Analytics of Cloud Computing Ecosystems

Abstract

Big Data, adaptation and analytics within Cloud Computing ecosystem are integrated in this study as a detail solution of their transformative role in contemporary business environment. Big Data and Cloud Computing convergence allows for the production of dynamic and scalable platforms that can process huge volumes of data for businesses which are able to make enhanced decision making, predictive capabilities and business operations. In this research we look at data storage, data processing frameworks and real time analytics independent of their integration into Cloud and analyze about the key components that make the difference when it comes to Big Data adaptartion. Finally, the study also points out that organizations will face challenges as well as opportunities that exist in the Cloud due to growing data management demands, with regards to issues of data security and privacy issues, and optimizing the infrastructure to support these data demands. It also describes various Cloud based analytical tools and technologies on which meaningful insights can be derived from large datasets. The book discusses key methodologies such as machine learning, artificial intelligence and data mining, which help to show how they are used in Cloud ecosystems to extract the business intelligence, that is, actionable information. Additionally, the paper explores the application of Big Data analytics and Cloud Computing in specific industry such as healthcare, finance, and retail. The study concludes by explaining how the integration of this nature will emerge in future years and how emerging technologies such as Edge Computing and Serverless Architecture are going to shape the next wave of the Big Data and Cloud Computing evolvement. The study presents an exhaustive framework of the intricate relationship between these two vital aspects, which collectively bring tremendous impetus toward the industrial revolution of the ages.