Our world is becoming increasing Funesian in that we are perceiving and storing more and more information in the form of data. But, as with Funes, access to information is not the same as understanding. Are we also better at extracting meaning from all of this data? What does understanding rely on – is it only possible through sophisticated data-processing techniques or is something else required? This paper will briefly discuss three common pitfalls related to the challenge of extracting meaning from data.