Internet of Everything Advancement Study in Data Science and Knowledge Analytic Streams

Abstract

Internet of Everything (IoE) generates a massive amount of diverse data. To manage this, data is stored using a special method called a "column-oriented relational framework." In IoE databases, there are lots of rows (data points) but fewer columns (data types). A column-oriented approach helps improve performance and manage this large amount of data more efficiently. The way data is stored in these systems can sometimes lead to problems like data inconsistency and integrity issues, especially when dealing with different types of data in the same database. Using a column-oriented framework helps address these issues and makes it easier to store and access data quickly. Analytics is crucial in data science. It helps in understanding and using the data effectively. Since technology and business needs keep changing, analytics is an ongoing process. Two data scientists might solve the same problem in different ways, showing how flexible and creative analytics can be. The main goals are to create and study new data models, frameworks, and algorithms for handling IoE data. These advancements aim to improve how we manage IoE databases and discover valuable insights from the data. The research focuses on improving the way IoE data is stored and managed using advanced techniques, addressing storage challenges, and enhancing data analysis to adapt to ever-changing needs.