Good quality data is the basis for high quality models and valuable data insights. But isn't it annoying how often your data is riddled with those pesky humans? Human involvement in data creation often introduces errors, misunderstandings, and biases that can compromise data integrity. This talk will explore how human factors influence the data creation process and what we as data professionals can do to account for this in our data interpretation and usage.