The real work of data science: turning data into information, better decisions, and stronger organizations
"The essential guide for data scientists and for leaders who must get more from their data science teams. The Economist boldly claims that data are now 'the world's most valuable resource.' But, as Kenett and Redman so richly describe, unlocking that value requires far more than...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ, USA
Wiley
[2019]
|
| Schlagworte: | |
| Online-Zugang: | FHA01 TUM01 UBR01 UER01 Volltext |
| Zusammenfassung: | "The essential guide for data scientists and for leaders who must get more from their data science teams. The Economist boldly claims that data are now 'the world's most valuable resource.' But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. Individual data scientists must fully extend themselves. They must make sure they understand the real problems their companies and agencies face, they must build trust with decision-makers, deal with quality issues, help decision makers become more demanding customers of data science, and they must teach their colleagues how to understand and interpret data science--even conduct basic analyses themselves. Further up in the management chain, managers of data science teams must help senior leaders understand where data and data science fit, ensure their teams are placed in the right spots organizationally, and put in place programs that help the entire organization become data-driven. This Kenett and Redman claim, is the 'real work of data science.' And it is this work that will spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is 'the most valuable resource'"-- A higher calling -- The difference between a good data scientist and a great one -- Learn the business -- Understand the real problem -- Get out there -- Sorry, but you can't trust the data -- Make it easy for people to understand your insights -- "When the data leaves off and your intuition takes over -- Take accountability for results -- What does it mean to be 'data-driven' -- Rooting out bias in decision-making -- Teach, teach, teach -- Evaluating data science outputs more formally -- Educating senior leaders -- Putting data science, and data scientists, in the right spots -- Moving up the analytics maturity ladder -- The industrial revolutions and data science -- Epilogue -- Appendix A. Skills of the data scientist -- Appendix B. Data defined -- Appendix C. Questions to help evaluate the outputs of data science -- Appendix D. Ethical considerations and today's data scientist -- Appendix E. Recent technical advances in data science |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781119570714 9781119570790 |
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| 520 | 3 | |a "The essential guide for data scientists and for leaders who must get more from their data science teams. The Economist boldly claims that data are now 'the world's most valuable resource.' But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. Individual data scientists must fully extend themselves. They must make sure they understand the real problems their companies and agencies face, they must build trust with decision-makers, deal with quality issues, help decision makers become more demanding customers of data science, and they must teach their colleagues how to understand and interpret data science--even conduct basic analyses themselves. Further up in the management chain, managers of data science teams must help senior leaders understand where data and data science fit, ensure their teams are placed in the right spots organizationally, and put in place programs that help the entire organization become data-driven. This Kenett and Redman claim, is the 'real work of data science.' And it is this work that will spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is 'the most valuable resource'"-- | |
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| spelling | Kenett, Ron 1950- Verfasser (DE-588)13007120X aut The real work of data science turning data into information, better decisions, and stronger organizations Ron S. Kenett, Thomas C. Redman Hoboken, NJ, USA Wiley [2019] © 2019 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "The essential guide for data scientists and for leaders who must get more from their data science teams. The Economist boldly claims that data are now 'the world's most valuable resource.' But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. Individual data scientists must fully extend themselves. They must make sure they understand the real problems their companies and agencies face, they must build trust with decision-makers, deal with quality issues, help decision makers become more demanding customers of data science, and they must teach their colleagues how to understand and interpret data science--even conduct basic analyses themselves. Further up in the management chain, managers of data science teams must help senior leaders understand where data and data science fit, ensure their teams are placed in the right spots organizationally, and put in place programs that help the entire organization become data-driven. This Kenett and Redman claim, is the 'real work of data science.' And it is this work that will spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is 'the most valuable resource'"-- A higher calling -- The difference between a good data scientist and a great one -- Learn the business -- Understand the real problem -- Get out there -- Sorry, but you can't trust the data -- Make it easy for people to understand your insights -- "When the data leaves off and your intuition takes over -- Take accountability for results -- What does it mean to be 'data-driven' -- Rooting out bias in decision-making -- Teach, teach, teach -- Evaluating data science outputs more formally -- Educating senior leaders -- Putting data science, and data scientists, in the right spots -- Moving up the analytics maturity ladder -- The industrial revolutions and data science -- Epilogue -- Appendix A. Skills of the data scientist -- Appendix B. Data defined -- Appendix C. Questions to help evaluate the outputs of data science -- Appendix D. Ethical considerations and today's data scientist -- Appendix E. Recent technical advances in data science Wissensmanagement (DE-588)4561842-2 gnd rswk-swf Datenauswertung (DE-588)4131193-0 gnd rswk-swf Knowledge management MATHEMATICS ; Probability & Statistics ; General SCIENCE ; Experiments & Projects BUSINESS & ECONOMICS ; Statistics Electronic books Datenauswertung (DE-588)4131193-0 s Wissensmanagement (DE-588)4561842-2 s DE-604 Redman, Thomas C. Verfasser (DE-588)1189763362 aut Erscheint auch als Druck-Ausgabe 978-1-119-57070-7 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119570790 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Kenett, Ron 1950- Redman, Thomas C. The real work of data science turning data into information, better decisions, and stronger organizations Wissensmanagement (DE-588)4561842-2 gnd Datenauswertung (DE-588)4131193-0 gnd |
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| title | The real work of data science turning data into information, better decisions, and stronger organizations |
| title_auth | The real work of data science turning data into information, better decisions, and stronger organizations |
| title_exact_search | The real work of data science turning data into information, better decisions, and stronger organizations |
| title_full | The real work of data science turning data into information, better decisions, and stronger organizations Ron S. Kenett, Thomas C. Redman |
| title_fullStr | The real work of data science turning data into information, better decisions, and stronger organizations Ron S. Kenett, Thomas C. Redman |
| title_full_unstemmed | The real work of data science turning data into information, better decisions, and stronger organizations Ron S. Kenett, Thomas C. Redman |
| title_short | The real work of data science |
| title_sort | the real work of data science turning data into information better decisions and stronger organizations |
| title_sub | turning data into information, better decisions, and stronger organizations |
| topic | Wissensmanagement (DE-588)4561842-2 gnd Datenauswertung (DE-588)4131193-0 gnd |
| topic_facet | Wissensmanagement Datenauswertung |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/9781119570790 |
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