Big Data Concept

  Introduction In the era of big data, the volume, variety, and velocity of information have surged, creating opportunities for deeper insights across diverse domains. Cross-modal data integration involves combining heterogeneous data types—such as text, images, and sensor data—into a unified framework for comprehensive analytics. This approach leverages the strengths of each modality to enhance understanding, improve decision-making, and uncover hidden patterns that single-mode analysis might miss. This chapter explores the techniques, challenges, and applications of cross-modal data integration in big data, highlighting its potential to revolutionize fields like healthcare, environmental monitoring, and smart cities. Understanding Cross-Modal Data Cross-modal data refers to information from different sources or formats that capture complementary aspects of a phenomenon. Each modality provides unique perspectives: Text Data : Includes documents, social media posts, and reports,...