You are leaving out a very important part of the sentence - "until we say what caused it". If you listen to the first few lectures you'll understand exactly what he intends with this sentence.
To your point...Data has context. It has a source. It likely has flaws and/or (so to speak) bias. To get anything of it It's essential to understand what went into it. Else you'll deceive yourself or your stakeholders and bad decisions will be made.
Thanks, though I actually meant to copy the entire thing (my fault).
My point was that a lot of people working in data analysis would (strongly) disagree with the idea that we need to model the data in order to do anything with it. Visualisations and tabulations can tell a lot without any mathematical formalism.
“What caused it” is the answer, and a graph can reveal just as easily as it can conceal the cause. Lies, damn lies, and statistics.