Digital twins, BIM-GIS integration, and modern reality capture workflows all depend on one foundational requirement: geospatial alignment. Yet in practice, lidar, photogrammetry, orthoimagery, and elevation data are often created from varying acquisition methods and coordinate reference systems, introducing misalignment that impacts accuracy, analysis, and downstream decision-making. This presentation demonstrates how geodetically inconsistent datasets can compromise the reliability of a digital twin, even when the underlying data itself is high quality. Using a real-world multi-source dataset consisting of terrestrial lidar, drone-derived photogrammetric point clouds, orthoimagery, and elevation models, attendees will see how coordinate inconsistencies create visible and measurable errors across both 2D and 3D environments. Using the latest version of Global Mapper and the integrated GeoCalc engine, the session walks through how disparate datasets can be transformed into a unified geospatial framework with consistent horizontal and vertical reference systems. Attendees will also see how new capabilities, including automated point cloud analysis and enhanced reality capture workflows, support more scalable, accurate, and operationally efficient geospatial processing. The result is a more accurate, trustworthy, and operationally useful product, along with a practical understanding of why geodetic integrity remains foundational to modern geospatial workflows.