Keywords: big data, professionalism
Big data is everywhere. Big theory is not. This leads to big challenges. In a world where we can put a price on almost anything, it is tempting, and it appears appropriate, to analyze big data for big solutions almost directly. However, in the economical rush to big solutions, we may skip developing big theories and understanding of the underlying causes, processes, and effects not necessary to get to apparent fixes. This talk will review the big picture, examples where we went from data to apparent solutions without understanding, and make the case that we need big theory, too, to address the big challenges.