2017/06/29 by Longbing Cao · 1 citation
Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Research Data Management Practices #Scientific Computing and Data Management #cs.CY
paper · pdf · doi:10.1145/3076253
published as ACM Computing Surveys, 50(3), 43:1-42, 2017
openalex publication_date 2017/06/29 · arxiv created 2020/07/01 · arxiv updated 2020/07/08 · openalex created_date 2020/11/23 · openalex updated_date 2026/08/04
The twenty-first century has ushered in the age of big data and data economy, in which data DNA, which carries important knowledge, insights and potential, has become an intrinsic constituent of all data-based organisms. An appropriate understanding of data DNA and its organisms relies on the new field of data science and its keystone, analytics. Although it is widely debated whether big data is only hype and buzz, and data science is still in a very early phase, significant challenges and opportunities are emerging or have been inspired by the research, innovation, business, profession, and education of data science. This paper provides a comprehensive survey and tutorial of the fundamental aspects of data science: the evolution from data analysis to data science, the data science concepts, a big picture of the era of data science, the major challenges and directions in data innovation, the nature of data analytics, new industrialization and service opportunities in the data economy, the profession and competency of data education, and the future of data science. This article is the first in the field to draw a comprehensive big picture, in addition to offering rich observations, lessons and thinking about data science and analytics.