Journal
2023 5TH GLOBAL POWER, ENERGY AND COMMUNICATION CONFERENCE, GPECOM
Volume -, Issue -, Pages 554-559Publisher
IEEE
DOI: 10.1109/GPECOM58364.2023.10175760
Keywords
Big Data; Data mining; Social networking; Big Data analytics; Decision making; Information technology; Internet of Things; Cloud computing
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In recent years, the rapid growth of data generation, Internet applications, mobile applications, and network-connected sensors has led to the emergence of big data. Cloud computing and the Internet of Things have further contributed to the dramatic growth of data. This article provides an overview of big data, its features, applications, and implementation, and discusses challenges and technologies related to big data, such as data analysis, storage, and visualization, as well as cloud computing, IoT, and data centers.
In recent years, data generation is increasing on a large scale and fast pace, and the development of Internet applications, mobile applications, and network-connected sensors has also increased widely. These applications and extensive internet connections continuously produce a large volume of data, with a wide diversity and different structures, which is called big data. At the same time, technologies related to big data are also developing. The rapid growth of cloud computing and the Internet of Things (IoT) is accelerating the dramatic growth of data generation. Sensors around the world are collecting and transmitting data that will be stored and processed in the cloud, and the era of big data is coming. In this article, first, an overview of big data and the definitions of its features are explained, and then the applications of big data in different fields are examined and the challenges facing it are discussed. Finally, technologies related to big data in the field of big data analysis, data storage technologies, and visualization tools are proposed and cloud computing, IoT, and data center are examined as new technologies that are closely related to big data. The main goal of this article is to provide a comprehensive overview of big data and examine and explain various aspects of its applications and implementation.
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