"A common refrain among the data science community is that existing business analysts are too burdened with their assumptions and bias from their existing work to be effective with big data, working with predominately internal data, usually at some level of aggregation as well. Data scientists, the argument goes, are more “scientific” and use machine learning algorithms to allow the data to speak for itself. Neither of these arguments is particularly valid. No matter how much machine learning is employed, at some point the data scientist has to build a model and at this point their experience and “bias” come into play."
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