Comment by hbarka

In the real world, data is never this clean. Majority of the time is data quality work because you will see outliers that might be due to measurement error, calibration, process changes. It requires familiarity with the process and having an understanding and intuition for why the shape of the data distribution in a process is the way it is. Because ad-hoc data visualization and exploration is critical here, enterprise requirements need mature tools that can be used quickly. BYOT and DIY code for an SPC Cpk chart is not what you want to be doing.