Data Science: A Comprehensive Overview

被引:236
作者
Cao, Longbing [1 ]
机构
[1] Univ Technol Sydney, Fac Engn & IT, UTS Adv Analyt Inst, POB 123 Broadway, Sydney, NSW 2007, Australia
基金
澳大利亚研究理事会;
关键词
Big data; data analysis; data analytics; advanced analytics; big data analytics; data science; data engineering; data scientist; statistics; computing; informatics; data DNA; data innovation; data economy; data industry; data service; data profession; data education; BIG DATA; STATISTICS; ANALYTICS; FUTURE; GUIDE;
D O I
10.1145/3076253
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The 21st 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 article 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.
引用
收藏
页数:42
相关论文
共 178 条
[1]   Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research [J].
Agarwal, Ritu ;
Dhar, Vasant .
INFORMATION SYSTEMS RESEARCH, 2014, 25 (03) :443-448
[2]  
AGIMO, 2013, AGIMO BIG DAT STRAT
[3]  
Anderson P, 2014, PROCEEDINGS OF THE 45TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE'14), P145
[4]  
[Anonymous], 1996, IFSC96
[5]  
[Anonymous], 2016, PRED AN TOD
[6]  
[Anonymous], 2016, Google Trends
[7]  
[Anonymous], 2014, P SO AFR I COMP SCI
[8]  
[Anonymous], 2011, Data Analysis: What Can Be Learned From the Past 50 Years
[9]  
[Anonymous], 2016, UK BIG DAT
[10]  
[Anonymous], 2016, 37. AlphalambdaepsilonxialphanudeltarhoomicronpiomicronAlambdaomicronupsilon - Alphaiotagammaupsilonpitauiotaάdeltaomicronupsilon, Epsilon. (2016), DeltaiotaalphasigmaupsilonnuomicronrhoiotaalphakappaAz rhoomicronAz pirhoomicronsigmaomegapiiotakappaAnu deltaepsilondeltaomicronmuέnuomeganu alphapiό tauetanu EpsilonEpsilon sigmatauiotasigma EtaPiAlpha: Eta pirhoόsigmaphialphataueta alphapiόphialphasigmaeta tauomicronupsilon DeltaEpsilonEpsilon epsilonnuόpsiepsiloniota tauetasig