This research study explores Design Science Research Method (DSRM) in creating an artifact that integrates spatial data analytics and data mining techniques to better understand social inequalities in the United States. This design combines two methodologies into one, while utilizing US Census data. This new method and authoritative data consider location and socioeconomic attributes of populations to assess disparities in a practical and structured approach, as well to generalize findings in a replicable manner. This research proposes statistical models, mapping, and other visualizations to investigate inequalities with the use of Stata, ArcGIS Pro, and python. This method also proposes a statistical hypothesis to test and validate the model with a significance level of five percent. This artifact would be applicable to many subjects, including healthcare insurance disparities, internet coverage access gaps, and racial residential segregation for communities at different census geographies, like zip code tabulation areas (ZTCAS), tracts, or blocks.