Efficient Data Management Strategies for Cloud Computing Environments

Abstract

Abstract: Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as One drive, iCloud and Google One) and allows them to cut costs on hardware and IT support. Variety of data to be analysed continues to quickly rise as new applications like social network analysis, semantic Web analysis, and bioinformatics network analysis proliferate. The problem of efficiently managing and analysing massive amounts of data is both fascinating and important. There has been a lot of focus on big data lately, from researchers to business leaders to policymakers. From both a technical and practical perspective, this paper presents numerous methods for processing massive amounts of data. We begin by discussing the most important aspects of big data analytics and processing from the perspective of cloud data management and the mechanisms involved in processing large amounts of data. This covers the cloud computing platform, cloud architecture, cloud database, and data storage scheme. It examines the responsibilities of hosting businesses who own and run cloud computing datacentres (like Amazon) with regards to data security and privacy. As an example, it takes into account the fact that many cloud service providers (like Dropbox and Salesforce) really rent out space in the cloud' from larger hosting corporations. And it examines the business and private ‘clouders’ using these services. As we all familiar with cloud computing, it’s not a latest technology, rather we can mention it as an emerging technology where most of the industry is trying to store not only its crucial data for redundancy but also looking for the service management. In that scenario first thing comes in mind is management of data in most efficient way possible.