I was recently a panelist for a Dataversity webinar/discussion focused on the future of data modeling tools, functionality, and practice. Given the holiday season, the panelists discussed their wish list for modeling tools – from currently practical (but maybe not economically viable) to futuristic (e.g., using a 3D printer to print models for model reviews, using Google Glass to move objects around on the model).
Of course, many modeling tools already support a vast array of functionality and sometimes can be difficult to use some of the non-core functionality without experiencing some unintended consequences, and so more intelligent guides and better semantics in the modeling tool will make these easier to use – so modelers can focus more on modeling and less on the technology.
More important than the technology – as important and interesting as that is – is having solid processes and modeling standards in place to ensure better model quality, reuse, and understandability.
