In practice, "data" means a set of observations collected by humans- who have inherent biases that influence the collection.
I'm not talking specifically about cultural biases like racial stereotypes etc. Confirmation bias is a thing, there's nothing stopping a researcher from making those observations that confirm their favoured theory and contradict all others.
Then of course there is sampling error. Just because you have a set of data that you collected "at random" doesn't mean that this dataset is representative of the population you are interested in. Let alone the fact that it's very hard to collect a truly random set of observations about processes that we don't understand to begin with.
The kind of data you're describing is an ideal, a principle that we all aspire to. It's far from the reality in practice.
I'm not talking specifically about cultural biases like racial stereotypes etc. Confirmation bias is a thing, there's nothing stopping a researcher from making those observations that confirm their favoured theory and contradict all others.
Then of course there is sampling error. Just because you have a set of data that you collected "at random" doesn't mean that this dataset is representative of the population you are interested in. Let alone the fact that it's very hard to collect a truly random set of observations about processes that we don't understand to begin with.
The kind of data you're describing is an ideal, a principle that we all aspire to. It's far from the reality in practice.