Scientists across all disciplines increasingly rely on machine learning code to analyze the vast quantity of data that is now commonplace, rapidly growing in volume and complexity. As the compelling trends and outliers are identified, careful and close inspection will still be necessary to disentangle the astrophysics from, say, systematics and false positives. It is clearly necessary to migrate to new technologies to facilitate scientific analysis and exploration. Astrophysical data is inherently multi-parameter, with the spatial dimensions at the core of imaging, spectral, time-domain and simulation data. The arrival of mainstream virtual-reality (VR) headsets and increased GPU power, as well as the availability of versatile development tools for video games, has enabled scientists to deploy such technology to effectively interrogate and interact with complex multidimensional data. In this paper we present development and results from custom-built interactive VR tools, called the IDAVIE suite, that are informed and driven by research on galaxy evolution, cosmic web large-scale structure, galaxy-galaxy interactions, and gas/kinematics of nearby galaxies in survey and targeted observations. The Era of Big Data ushered in by the SKA and its Pathfinders challenges our storage, calibration, reduction and refinement methods, and it also demands innovative ways to interrogate the data at intuitive -- leveraging visual perception -- levels necessary for new discovery.