Data Science vs Statistics
According to a recent poll ( http://www.kdnuggets.com/2013/05/poll-results-with-big-data-statistics-will-become-more-important.htm ) the big majority (68%) of KDnuggets audience thought that in the Era of Big Data, Statistics will become more important, as the foundation of Data Science.
By paraphrasing an old definition of mine for Computational Statistics (Computational Statistics & Data Analysis 23: 191–193, 1996) it can be said that "Data Science is Statistics in Computer and Internet era."..
Statisticians nowadays, have not only to deal with abundant data but also with new ones as well as with more complex data structure. In order to face these data the new technologies are playing an important role.All this has strongly affected the paradigm and reasoning of the classical statistics mainly based on the sample theory and related data analysis methods.
So far the main goal of Data Science is to provide a suitable statistical framework for studying the problem of gaining knowledge, making predictions, making decisions or constructing models for specific domains.Where modeling should be intended in a soft way (soft modeling) by relaxing strong distributional hypotheses toward structural ones.