The principle drawback of positivism's reliance on large data sets for the bulk of their evidence is their unquestioning approach to the results. Because positivism assumes data, statists, and numbers to be objective truths, they fail to account for the possibility of skewed results. Data can be inaccurate if collected badly. Especially with large data samples which rely on large bodies of people providing data, there is a risk of unauthentic and constrained responses.
Unlike qualitative methods, there is no direct supervision over the responses and nothing to guarantee that respondents are answering truthfully and authentically. A respondent may simply choose to randomly tick boxes to save time. At the same time, respondents who do seek to answer truthfully may be constrained by the options provided. If the participant's honest and authentic response is not among one of the provided responses, the data suffers because it does not capture the true response. Large data sets are only as good as the the methods through which the data is collected. Therefore, an over-reliance on data as objective truth fails to account for human error in collection.