Advances in Data Systems

Abstract

In today’s world of technology, data systems have gained prominence in all arenas including business, healthcare, education and science. This review of literature provides a guide through the most recent trends in data systems and analysis, stressing that it is necessary to be aware of contemporary changes. The search strategy includes reliable databases like IEEE Xplore, ACM Digital Library and Google Scholar with keywords Data Systems, Database Modelling and Big Data. Finally, the historical context follows from conventional databases into modern big data systems to NoSQL. Important notions comprise basic ones such as data modelling, storage, retrieval and processing taking into account problems arising in current systems. The heart of the essay goes into developments on data models particularly graph databases, document stores and columnar databases, developments in NoSQL, real time analysis, hybrid data management, data lakes and data warehouses. Identifying challenges and open issues in the data systems domain opens new opportunities for future research directions. The conclusion underscores the importance of staying abreast of advancements in harnessing the full potential of data, setting the stage for the key question: To what extent do recent advancements in data modelling contribute to enhanced scalability, flexibility, and efficiency in handling diverse data structures and volumes?