Analysis of big data in computer graphics

In this article, an overview of the aspects of big data analysis and representation in computer graphics is presented, creating new prospects for the development and improvement of applications for processing graphic information, visualization, and simulation. Thanks to advancements in data processing and analysis technologies, computer graphics can become even more realistic, interactive, and efficient. Data can come from various sources, including 3D scanning, modeling, sensors, video cameras, games, and simulations. Storing large volumes of graphic data requires effective solutions such as distributed file systems, databases, and cloud services. The review analysis covers the processing of big data, including machine learning, image recognition algorithms, parallel computing, and resource optimization. Special attention is paid to the challenges and prospects of using big data in computer graphics, which includes improving the quality of graphic data analysis, optimizing the rendering of extremely large images, and integration with third-party systems.