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DATA SCIENCE: CHALLENGES AND TRENDS
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DATA SCIENCE: CHALLENGES AND TRENDS (2019)DATA SCIENCE: CHALLENGES AND TRENDSData Science: A Comprehensive Overview (2020)Data Science: A Comprehensive…On Developing Data Science (2019)On Developing Data ScienceStatistics: a Data Science for the 21st Century (2015)Statistics: a Data Science fo…Intrinsic Relations between Data Science, Big Data, Business Analytics and Datafication (2014)Intrinsic Relations between D…Data Scientist: The Engineer of the Future (2014)Data Scientist: The Engineer …Big Data, Big Questions| The Big Data Divide (2014)Big Data, Big Questions| The …Data Science and Prediction (2012)Data Science and PredictionTransdisciplinarity: a new mode of governing science? (2006)Transdisciplinarity: a new mo…Problem based learning (2003)Statistical Analyses and Reproducible Research (2007)Reproducible Research in Computational Science (2011)Data Science (2017)What makes Data Science different? A discussion involving Statistics2.0 and Computational Sciences (2018)Business Research: A Practical Guide for Undergraduate and Postgraduate Students (2009)Big data: The next frontier for innovation, competition, and productivity (2011)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Real-Time Grain Commodities Price Predictions in South Africa: A Big Data and Neural Networks Approach (2016)Process Mining (2011)Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)How Data Science Workers Work with Data (2019)Human-AI Collaboration in Data Science (2019)A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks (2020)Challenges and opportunities with big data (2012)Big data and its technical challenges (2014)Sports analytics and the big-data era (2018)AI for the Common Good?! Pitfalls, challenges, and ethics pen-testing (2019)AI in Finance: A Review (2020)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)Conjectures and Refutations (1963)To Explain or to Predict? (2010)Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research (2014)‘Personal data literacies’: A critical literacies approach to enhancing understandings of personal digital data (2018)How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks (2018)The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts (2015)Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram (2018)When data is capital: Datafication, accumulation, and extraction (2019)Transdisciplinarity: Between mainstreaming and marginalization (2012)Transdisciplinary research in sustainability science: practice, principles, and challenges (2012)The politics of co-production: participation, power, and transformation (2019)
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References

  • 2012Data Science and Prediction915 cited
  • 2020Data Science: A Comprehensive Overview216 cited
  • 2014Data Scientist: The Engineer of the Future150 cited
  • 2006Transdisciplinarity: a new mode of governing science?137 cited
  • 2014Big Data, Big Questions| The Big Data Divide125 cited
  • 2015Statistics: a Data Science for the 21st Century65 cited
  • 2014Intrinsic Relations between Data Science, Big Data, Business Analytics and Datafication27 cited
  • 2019On Developing Data Science10 cited

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