Geospatial analysis enhances traditional data analysis by adding a geographic and temporal context, transforming raw spatial data into actionable insights crucial for various fields like urban planning, disaster management, public health, and business intelligence. This analytical approach uses tools such as geographic information systems (GIS) to interpret spatial data, enabling the identification of patterns and relationships that are invisible without a spatial context. By using vector and raster data formats, as well as real-time data from GPS devices and satellite imagery, geospatial analysis aids in better decision-making, resource optimization, risk management, and innovative problem-solving. The application of these insights ranges from guiding urban development and managing environmental changes to improving public health strategies and enhancing business operations. Platforms like Felt, an AI-native cloud-based Web GIS, facilitate the efficient handling and visualization of geospatial data, enabling teams to quickly turn complex datasets into clear, actionable insights without the need for extensive coding.