Since its introduction in 2006, differential privacy has emerged as a predominant statistical tool for quantifying data academic works. Yet despite the plethora of research and open-source utilities that have accompanied rise, with limited exceptions, failed to achieve widespread adoption enterprise domain. Our study aims shed light on fundamental causes underlying this academic-industrial util...