More than 50 years ago, John Tukey called for a reformation of academic statistics. In `TheFuture of Data Analysis', he pointed to the existence of an as-yet unrecognized science, whosesubject of interest was learning from data, or `data analysis'. Ten to twenty years ago, JohnChambers, Bill Cleveland and Leo Breiman independently once again urged academic statisticsto expand its boundaries beyond the classical domain of theoretical statistics; Chambers calledfor more emphasis on data preparation and presentation rather than statistical modeling; andBreiman called for emphasis on prediction rather than inference. Cleveland even suggested thecatchy name \Data Science" for his envisioned eld.A recent and growing phenomenon is the emergence of \Data Science" programs at majoruniversities, including UC Berkeley, NYU, MIT, and most recently the Univ. of Michigan, whichon September 8, 2015 announced a $100M \Data Science Initiative" that will hire 35 new faculty.Teaching in these new programs has signi cant overlap in curricular subject matter with tradi-tional statistics courses; in general, though, the new initiatives steer away from close involvementwith academic statistics departments.