Modern data analysis and research projects often incorporate multi-dimensional data from several sources, and new insights are increasingly driven by the ability to interpret data in the context of other data. Glue is a graphical environment built on top of the standard scientific Python stack to visualize relationships within and between data sets. With Glue, users can load and visualize multiple related data sets simultaneously, specify the logical connections that exist between data, and Glue transparently uses this information as needed to enable visualization across files. Glue includes an easy mechanism for users to customize many aspects of the application, and also features a plugin system for third-party packages to provide further customization, for example custom data viewers. In this talk, I will give an overview of the Glue package, and will demonstrate the latest functionality including recently added viewers based on VisPy and OpenGL to interactively explore data in 3D. Glue is currently being used to analyze astronomical, medical, and other scientific data, and is also being used by data scientists outside of academia. For a quick preview of what Glue can do, you can view the following 2-minute introductory video.