Council Post: Do We Need More Data Or More Science In Data Science?

Is the success of Google that of the algorithms or that of data? Today's fascination with artificial intelligence (AI) reflects both our appetite for data and our excitement about the new opportunities in machine learning. Here, I argue that newcomers to the field of data science are blinded by the shiny object of magical algorithms -- and that they forget the critical infrastructures that are needed to create and to manage data in the first place. There are now many companies that provide AI services. An attractive offer should affirm all of the above -- the sole expertise in analyses and algorithms is generally insufficient, as it does not necessarily address the data part of the equation.