Big data problem taxes computation resources in many ways including RAM, storage, swapping, ability to parallelize, and the limitations of specific software packages to even perform the operations. There is no conventional way to estimate spacial models of this size. As a result we have been required to creatively reform matrix objects, use relatively obscure linear algebra relationships, break operations up into multiple discrete tasks, and consider hardware issues in new ways. The current solution is written in C++ code to run on AWS, which is labor intensive and ultimately expensive. Human life is more complex, data oriented, and technical than ever before. Every field, including political science, needs to understand that it is also a data science field. Based on: Gill, Jeff, 2021. Political Science Is a Data Science. The Journal of Politics, 83(1), pp.1-7.