CLOUD COMPUTING AND DATA MANAGEMENT

Abstract

Decentralized data storage, processing, and management structures by companies have significantly increased due to the availability of processing power over the internet that is, elastic, on demand and cost effective. Education, health, commercial and government services are able to take advantage of the above assistance only in terms of “capacity and number of ports” without being burdened in procurement of any physical infrastructure. Management of data in a cloud area must take into account the following: timely data collection, storage, integration, protection, switching and analysis of volume data that can be structured and unstructured. Cloud-based data management systems offer capabilities for, but are not limited to, real-time collaboration, high-availability, disaster recovery and business continuity, and lower capital expenditure. On the contrary, the fast-paced cloud expansion also poses challenges in regards to data control, security attention, compliance with regulations, and technological overreliance. Today, fast-growing trend capabilities of the artificial intelligence, machine learning, edge and fog computing, big data models, and help in further integration of cloud data management by means of providing systems that allow for orders and payments of the customer replacing the old servers and applications along with the receiving of new data within an electronic atmosphere. In the end, we have learned that cloud computing technologies should never be underestimated in terms of the efficient handling of large-scale volumes of data. It has made it possible for business organizations to be able to leverage on improvement levels of its operation, product/service innovation and digitalization areas but a perfunctory statement without the mention of robust governance and security edges may at the same time bring serious implications to data management efforts.