The emergence of the era of data science and analytics can be highlighted by three key indicators:
a disciplinary paradigm shift, or the shifting of data-centric disciplinary paradigms from one to another;
technological transformation, or the upgrading of data technology from one generation to another; and
innovative production, or the innovation of technical and practical data products.
We can define the disciplinary paradigm shift of data-oriented and data-centric research, innovation, and professions as moving from data analysis to data analytics, from descriptive analytics to deep analytics, and from data analytics to data science. The disciplinary paradigm shift promotes data-related technological transformation from large-scale data to big data, from business operational systems to business analytical systems, from the World Wide Web to the Wisdom Web, and from the Internet to the Internet of Everything (including mobile and social networks and the Internet of Things).
Innovative production in data and analytics can be represented by typical indicators-for example, from a digital to a data economy, from closed to open government, from e-commerce to online business, from landlines to smartphones, and from the Internet to mobile and social networks.
Note: Excerpted from "L. Cao. Data Science: Nature and Pitfalls, IEEE Intelligent Systems, Volume: 31, Issue: 5, 66-75, 2016"