Data virtualization enables users to access and manipulate data from multiple sources without the need to know where that data is stored or to move it to a central location, providing a unified view of data in real-time. Data visualization, on the other hand, presents raw data in graphical or visual formats, such as charts, graphs, maps, and infographics, making complex data patterns, trends, and insights more easily understandable. The two technologies cater to distinct aspects of data handling, with data virtualization focusing on integration and presentation differing from data visualization's focus on presentation. Data virtualization offers benefits like unified data access, data discovery, improved data quality, optimized resources, and enhanced decision-making capabilities, while data visualization enhances data accessibility, exploration, insights, and user experience. Understanding the key differences between these technologies is essential for businesses to use them effectively in their data-strategy goals.