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Data Literacy und Strategien der datengetriebenen Wertschöpfung

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  4. Vol. 62, Issue 2
  5. pp. 87–98

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Knuth, T. Data Literacy und Strategien der datengetriebenen Wertschöpfung. Der Betriebswirt, 62(2), 87-98. https://doi.org/10.3790/dbw.62.2.87
Knuth, Tobias "Data Literacy und Strategien der datengetriebenen Wertschöpfung" Der Betriebswirt 62.2, 2021, 87-98. https://doi.org/10.3790/dbw.62.2.87
Knuth, Tobias (2021): Data Literacy und Strategien der datengetriebenen Wertschöpfung, in: Der Betriebswirt, vol. 62, iss. 2, 87-98, [online] https://doi.org/10.3790/dbw.62.2.87
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Data Literacy und Strategien der datengetriebenen Wertschöpfung

Knuth, Tobias

Der Betriebswirt, Vol. 62 (2021), Iss. 2 : pp. 87–98

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Article Details

Publisher Name
Duncker & Humblot, Deutscher Betriebswirte Verlag
DOI
https://doi.org/10.3790/dbw.62.2.87
Language
German
Pages
12

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Author Details

Tobias Knuth lehrt als Dozent an der FOM Hochschule für Ökonomie & Management unter anderem Algorithmen und künstliche Intelligenz.

References

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  25. Shirani, A. (2016): „Idintifying Data Science and Analytics Compentencies Based on Industry Demand“, in: Issues In Information Systems 17.4.  Google Scholar
  26. Someh, I. A. et al. (2018): „Emergence of Data and Non-Data Team Networks: An Agent-Based Model“, in: 39th International Conference on Information Systems. San Francisco: Association for Information Systems.  Google Scholar
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  30. Yang, L. et al. (2014): A Cubic Framework for the Chief Data Officer: Succeeding in a World of Big Data. ESD Working Papers; ESD-WP-2014-34. Massachusetts Institute of Technology. Engineering Systems Division.  Google Scholar
  31. American Library Association (2006): „Presidential Committee on Information Literacy: Final Report“. URL: http://www.ala.org/acrl/publications/whitepapers/presidential (besucht am 14.02.2021).  Google Scholar
  32. Azevedo, A./Santos, M. (2008): „KDD, SEMMA and CRISP-DM: a parallel overview“, in: Proceedings of the IADIS European Conference on Data Mining. IADIS European Conference on Data Mining. Amsterdam.  Google Scholar
  33. Bersin, J./Zao-Sanders, M. (2020): Boost Your Team’s Data Literacy. Harvard Business Review. URL: https://hbr.org/2020/02/boost-your-teams-data-literacy (besucht am 15.02.2021).  Google Scholar
  34. Best, J. (2012): Damned lies and statistics: untangling numbers from the media, politicians, and activists. Updated edition. Berkeley, California; London: University of California Press.  Google Scholar
  35. Buschman, B. J. (2009): „Information Literacy, ‚New‘ Literacies, and Literacy“, in: The Library Quarterly 79.1, S. 95–118.  Google Scholar
  36. Chapman, P. et al. (2000): CRISP-DM 1.0: Step-by-step data mining guide.  Google Scholar
  37. Davenport, T. H./Patil, D. J. (2012): Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review. URL: https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century (besucht am 17.07.2015).  Google Scholar
  38. Economist Intelligence Unit (2011): Big data: Harnessing a game-changing asset. Economist Intelligence Unit Limited.  Google Scholar
  39. Fabijan, A. et al. (2017): „The Evolution of Continuous Experimentation in Software Product Development: From Data to a DataDriven Organization at Scale“, in: 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). Buenos Aires: IEEE, S. 770–780.  Google Scholar
  40. Gray, J./Gerlitz, C./Bounegru, L. (2018): „Data infrastructure literacy“, in: Big Data & Society 5.2.  Google Scholar
  41. Günther, W. A. et al. (2017): „Debating big data: A literature review on realizing value from big data“, in: The Journal of Strategic Information Systems 26.3, S. 191–209.  Google Scholar
  42. Yang, L. et al. (2014): A Cubic Framework for the Chief Data Officer: Succeeding in a World of Big Data. ESD Working Papers; ESD-WP-2014-34. Massachusetts Institute of Technology. Engineering Systems Division.  Google Scholar
  43. Wolf, V./Stumpf-Wollersheim, J./Poprawa, M. (2020): „Digitale Transformation in kleinen und mittelständischen Unternehmen“, in: Der Betriebswirt 61.1, S. 43–53.  Google Scholar
  44. The Economist (2017): The world’s most valuable resource is no longer oil, but data. URL: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data (besucht am 15.02.2021).  Google Scholar
  45. Strauss, D. et al. (2014): „How to Establish a CDO Office in Your Organization“, in: The 8th Annual MIT Chief Data Officer & Information Quality Symposium. Unter Mitarb. von B. Woo.  Google Scholar
  46. Someh, I. A. et al. (2018): „Emergence of Data and Non-Data Team Networks: An Agent-Based Model“, in: 39th International Conference on Information Systems. San Francisco: Association for Information Systems.  Google Scholar
  47. Shirani, A. (2016): „Idintifying Data Science and Analytics Compentencies Based on Industry Demand“, in: Issues In Information Systems 17.4.  Google Scholar
  48. Schüller, K./Koch, H./Rampelt, F. (2021): Data-Literacy-Charta. Version 1.2. Berlin: Stifterverband.  Google Scholar
  49. Schüller, K./Busch, P./Hindinger, C. (2019): Future Skills: Ein Framework für Data Literacy. Arbeitspapier Nr. 47. Berlin.  Google Scholar
  50. Schield, M. (2005): „Information Literacy, Statistical Literacy, Data Literacy“, in: IASSIST Quarterly 28.2, S. 6.  Google Scholar
  51. Ridsdale, C. et al. (2015): Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report. Canada: Dalhousie University.  Google Scholar
  52. Qlik und Accenture (2020): The Human Impact of Data Literacy. URL: https://thedataliteracyproject.org/humanimpact (besucht am 26.02.2021).  Google Scholar
  53. Nie, Y. et al. (2019): „The influence of chief data officer presence on firm performance: does firm size matter?“, in: Industrial Management & Data Systems 119.3, S. 495–520.  Google Scholar
  54. Moore, R. J. (2014): Democratizing data: Why data literacy will be the most important new skill of the 21st century. VentureBeat. URL: https://venturebeat.com/2014/11/07/democratizing-data-why-data-literacy-will-be-the-most-important-new-skill-of-the-21st-century/ (besucht am 18.02.2021).  Google Scholar
  55. McAfee, A./Brynjolfsson, E. (2012): Big Data: The Management Revolution. Harvard Business Review. URL: https://hbr.org/2012/10/big-data-the-management-revolution (besucht am 17.07.2015).  Google Scholar
  56. Ludwig, T./Thiemann, H. 2020): „Datenkompetenz – Data Literacy“, in: Informatik Spektrum 43.6, S. 436–439.  Google Scholar
  57. Letouzé, E. et al. (2015): Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data. Data-Pop Alliance.  Google Scholar
  58. Krupka, D. (2020): „Dimensionen digitaler Souveränität — ein Überblick“, in: Schlüsselaspekte digitaler Souveränität. Gesellschaft für Informatik e.V., S. 4–7.  Google Scholar
  59. Heidrich, J./Krupka, D. (2018): „Data Literacy: Data Skills in der Breite der Hochschulausbildung“, in: Data Literacy und Data Science Education: Digitale Kompetenzen in der Hochschulausbildung. Gesellschaft für Informatik e.V.  Google Scholar
  60. Heidrich, J./Bauer, P./Krupka, D. (2018): Future Skills: Ansätze zur Vermittlung von Data Literacy in der Hochschulbildung. Arbeitspapier Nr. 37. Berlin: Hochschulforum Digitalisierung.  Google Scholar
  61. American Library Association (2006): „Presidential Committee on Information Literacy: Final Report“. URL: http://www.ala.org/acrl/publications/whitepapers/presidential (besucht am 14.02.2021).  Google Scholar
  62. Azevedo, A./Santos, M. (2008): „KDD, SEMMA and CRISP-DM: a parallel overview“, in: Proceedings of the IADIS European Conference on Data Mining. IADIS European Conference on Data Mining. Amsterdam.  Google Scholar
  63. Bersin, J./Zao-Sanders, M. (2020): Boost Your Team’s Data Literacy. Harvard Business Review. URL: https://hbr.org/2020/02/boost-your-teams-data-literacy (besucht am 15.02.2021).  Google Scholar
  64. Best, J. (2012): Damned lies and statistics: untangling numbers from the media, politicians, and activists. Updated edition. Berkeley, California; London: University of California Press.  Google Scholar
  65. Buschman, B. J. (2009): „Information Literacy, ‚New‘ Literacies, and Literacy“, in: The Library Quarterly 79.1, S. 95–118.  Google Scholar
  66. Chapman, P. et al. (2000): CRISP-DM 1.0: Step-by-step data mining guide.  Google Scholar
  67. Davenport, T. H./Patil, D. J. (2012): Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review. URL: https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century (besucht am 17.07.2015).  Google Scholar
  68. Economist Intelligence Unit (2011): Big data: Harnessing a game-changing asset. Economist Intelligence Unit Limited.  Google Scholar
  69. Fabijan, A. et al. (2017): „The Evolution of Continuous Experimentation in Software Product Development: From Data to a DataDriven Organization at Scale“, in: 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). Buenos Aires: IEEE, S. 770–780.  Google Scholar
  70. Gray, J./Gerlitz, C./Bounegru, L. (2018): „Data infrastructure literacy“, in: Big Data & Society 5.2.  Google Scholar
  71. Günther, W. A. et al. (2017): „Debating big data: A literature review on realizing value from big data“, in: The Journal of Strategic Information Systems 26.3, S. 191–209.  Google Scholar
  72. Heidrich, J./Bauer, P./Krupka, D. (2018): Future Skills: Ansätze zur Vermittlung von Data Literacy in der Hochschulbildung. Arbeitspapier Nr. 37. Berlin: Hochschulforum Digitalisierung.  Google Scholar
  73. Heidrich, J./Krupka, D. (2018): „Data Literacy: Data Skills in der Breite der Hochschulausbildung“, in: Data Literacy und Data Science Education: Digitale Kompetenzen in der Hochschulausbildung. Gesellschaft für Informatik e.V.  Google Scholar
  74. Krupka, D. (2020): „Dimensionen digitaler Souveränität — ein Überblick“, in: Schlüsselaspekte digitaler Souveränität. Gesellschaft für Informatik e.V., S. 4–7.  Google Scholar
  75. Letouzé, E. et al. (2015): Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data. Data-Pop Alliance.  Google Scholar
  76. Ludwig, T./Thiemann, H. 2020): „Datenkompetenz – Data Literacy“, in: Informatik Spektrum 43.6, S. 436–439.  Google Scholar
  77. McAfee, A./Brynjolfsson, E. (2012): Big Data: The Management Revolution. Harvard Business Review. URL: https://hbr.org/2012/10/big-data-the-management-revolution (besucht am 17.07.2015).  Google Scholar
  78. Moore, R. J. (2014): Democratizing data: Why data literacy will be the most important new skill of the 21st century. VentureBeat. URL: https://venturebeat.com/2014/11/07/democratizing-data-why-data-literacy-will-be-the-most-important-new-skill-of-the-21st-century/ (besucht am 18.02.2021).  Google Scholar
  79. Nie, Y. et al. (2019): „The influence of chief data officer presence on firm performance: does firm size matter?“, in: Industrial Management & Data Systems 119.3, S. 495–520.  Google Scholar
  80. Qlik und Accenture (2020): The Human Impact of Data Literacy. URL: https://thedataliteracyproject.org/humanimpact (besucht am 26.02.2021).  Google Scholar
  81. Ridsdale, C. et al. (2015): Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report. Canada: Dalhousie University.  Google Scholar
  82. Schield, M. (2005): „Information Literacy, Statistical Literacy, Data Literacy“, in: IASSIST Quarterly 28.2, S. 6.  Google Scholar
  83. Schüller, K./Busch, P./Hindinger, C. (2019): Future Skills: Ein Framework für Data Literacy. Arbeitspapier Nr. 47. Berlin.  Google Scholar
  84. Schüller, K./Koch, H./Rampelt, F. (2021): Data-Literacy-Charta. Version 1.2. Berlin: Stifterverband.  Google Scholar
  85. Shirani, A. (2016): „Idintifying Data Science and Analytics Compentencies Based on Industry Demand“, in: Issues In Information Systems 17.4.  Google Scholar
  86. Someh, I. A. et al. (2018): „Emergence of Data and Non-Data Team Networks: An Agent-Based Model“, in: 39th International Conference on Information Systems. San Francisco: Association for Information Systems.  Google Scholar
  87. Strauss, D. et al. (2014): „How to Establish a CDO Office in Your Organization“, in: The 8th Annual MIT Chief Data Officer & Information Quality Symposium. Unter Mitarb. von B. Woo.  Google Scholar
  88. The Economist (2017): The world’s most valuable resource is no longer oil, but data. URL: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data (besucht am 15.02.2021).  Google Scholar
  89. Wolf, V./Stumpf-Wollersheim, J./Poprawa, M. (2020): „Digitale Transformation in kleinen und mittelständischen Unternehmen“, in: Der Betriebswirt 61.1, S. 43–53.  Google Scholar
  90. Yang, L. et al. (2014): A Cubic Framework for the Chief Data Officer: Succeeding in a World of Big Data. ESD Working Papers; ESD-WP-2014-34. Massachusetts Institute of Technology. Engineering Systems Division.  Google Scholar

Abstract

Data have become ubiquitous in the 21st century. Companies can achieve a competitive advantage if they manage to utilise business data successfully, and a data strategy can help to become a data-driven company. In this article, three pillars are presented: data literacy as a central competence, data science as a specialisation, and the chief data officer as a C-level executive.

Table of Contents

Section Title Page Action Price
Tobias Knuth: Data Literacy und Strategien der datengetriebenen Wertschöpfung 1
Abstract 1
Zusammenfassung 1
Einführung 1
Data Literacy als zentrale Kompetenz 2
Data Science in Unternehmen 5
Chief Data Officers 7
Betriebliche Datenstrategie 8
Zusammenfassung und Ausblick 9
Literatur 1

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