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What Is Data Science?
6 references·1 citing·32 second hop
What Is Data Science? (2019)What Is Data Science?Understanding Data Science: An Emerging Discipline for Data Intensive Discovery. (2015)Understanding Data Science: A…The Proliferation of “Big Data” and Implications for Official Statistics and Statistical Agencies (2015)The Proliferation of “Big Dat…Capital in the Twenty-First Century (2014)Capital in the Twenty-First C…Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management (2013)Data Science, Predictive Anal…The Fourth Paradigm: Data-Intensive Scientific Discovery [Point of View] (2011)The Fourth Paradigm: Data-Int…Exploratory Data Mining and Data Cleaning (2003)Exploratory Data Mining and D…On Developing Data Science (2019)On Developing Data ScienceDesign of Experiments (1936)An overview of data warehousing and OLAP technology (1997)Data Cleaning: Problems and Current Approaches. (2000)Record linkage (2006)Overview and Framework for Data and Information Quality Research (2009)Data quality in internet of things: A state-of-the-art survey (2016)Latin American Economic Outlook (2009)Big data: The next frontier for innovation, competition, and productivity (2011)The World’s Technological Capacity to Store, Communicate, and Compute Information (2011)Big data: a revolution that will transform how we live, work, and think (2014)Big Data and Official Statistics: Opportunities, Challenges and Risks (2015)Access to New Data Sources for Statistics: Business Models and Incentives for the Corporate Sector (2017)Big data: the management revolution. (2012)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Critical analysis of Big Data challenges and analytical methods (2016)The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018)A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020)The Structure of Scientific Revolutions (1963)The magical number seven, plus or minus two: Some limits on our capacity for processing information. (1994)The Structure of Scientific Revolutions (1996)Capital is Back: Wealth-Income Ratios in Rich Countries 1700–2010 * (2014)Optimal Taxation of Top Labor Incomes: A Tale of Three Elasticities (2014)Taxing across Borders: Tracking Personal Wealth and Corporate Profits (2014)Big other: Surveillance Capitalism and the Prospects of an Information Civilization (2015)The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century (2015)The revenge of the places that don’t matter (and what to do about it) (2017)Why Most Published Research Findings Are False (2005)Why Most Published Research Findings Are False (2005)Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016)Exascale computing and big data (2015)Towards felicitous decision making: An overview on challenges and trends of Big Data (2016)How Data Science Workers Work with Data (2019)
this work references cited by second hop

References

  • 2014Capital in the Twenty-First Century14,423 cited
  • 2013Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management1,518 cited
  • 2003Exploratory Data Mining and Data Cleaning622 cited
  • 2011The Fourth Paradigm: Data-Intensive Scientific Discovery [Point of View]528 cited
  • 2015The Proliferation of “Big Data” and Implications for Official Statistics and Statistical Agencies44 cited
  • 2015Understanding Data Science: An Emerging Discipline for Data Intensive Discovery.34 cited

Cited by

  • 2019On Developing Data Science10 cited

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