There is not much attention paid these days to data reliability and validity (DR&V). Many data-scientific practitioners, especially those in Computer Science-IT Data Science (CS-IT Data Science), don’t get what the terms mean, especially for DR&AV work they might need to do routinely that they do not do at all. After all, we’ve got Big Data. And ultimately, “‘bigness’ mitigates whatever may be wrong with data that might bias findings from analytical operations on it, right? Maybe not. The statement is similar to other claims of CS-IT Data Science “evangelists,” such as “no need for statistics (i.e., ‘not
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