Data science and analytics: a new era

Abstract

The twenty-first century has ushered in a new age of data science and analytics. “Data science” as a scientific term was initially proposed about 15 years ago, and has since increasingly attracted attention and debate within statistics, analytics, computing, social science, and other scientific domains and disciplines. Although arguments have emerged from different communities such as, “How and why is data science different from statistics?” and “Why do we need data science when for decadeswe have had information science?”, it is undoubtedly a fact that data science is driving a new era of data-driven thinking, research, practice and education which goes far beyond the breadth and depth of previous efforts. In this data-intensive universe, data is a critical asset, and data science is the interdisciplinary core that drives new research, education and economy in many diverse areas. Although different definitions and interpretations exist, data science, as a scientific field, develops relevant methodologies, theories, technologies and applications for data, ranging from data capture, creation, representation, storage, search, sharing, privacy, security, modeling, analysis, learning, presentation and visualization, to integration across heterogeneous, interdependent complex resources for realtime decision-making, collaboration, value creation, and decision-support. The field encompasses the larger areas of statistics, data analytics, machine learning, big data management, and other disciplines, including complex systems, communications, social science, decision science, and management science.