Douglas A. Gray

The Art of Data Science (eBook, PDF)

A Practitioner's Guide

• Format: PDF

Produktbeschreibung

Author Doug Gray shares the most important lessons he has learned over the course of his 30+ year career in analytics and technology. Readers will witness the Analytical Sciences profession through the eye of a practitioner who has delivered solutions that generate hundreds of millions of dollars annually in business value.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 218
• Erscheinungstermin: 13. März 2025
• Englisch
• ISBN-13: 9781040310359
• Artikelnr.: 73154189

Autorenporträt

Douglas A. Gray is a practitioner, leader, and educator with over 30 years of experience leading award-winning teams at industry luminaries in analytics, including INFORMS Prize-winning American Airlines and Walmart. His teams have delivered advanced game-changing solutions in the airline operations, healthcare, and omnichannel retail supply chain domains, which deliver hundreds of millions of dollars in business value and economic impact annually. He teaches Analytics and AI Strategy at Southern Methodist University (SMU) in the Executive MBA, Executive Education, and MS Data Science programs, and has published over a dozen articles and two books on analytics best practices and applications.

Inhaltsangabe

About the Author Acknowledgements Foreword Introduction 1. Career Summary -
On Becoming a Practitioner and Leader 2. The Dual Challenge of the
Analytical Sciences Practitioner 3. Digital Transformation 4. Advanced
Analytics is Economically Transformational 5. Airworthy: American Airlines
Heavy Maintenance Planning & Scheduling 6. Consulting Concepts Learned from
Airworthy 7. A Modern Day Project Applying the Same Principles: Advanced
Analytics Commodity Case 8. Right Tool, Right Place, Right Time (with Nader
Kabbani) 9. Under Fire: Lessons from the Front; Revenue Management for
Manufacturing 10. Analytics Nontechnical Skills 11. Top 10 Analytics
Leadership Skills (with Tom Davenport) 12. Top 10 Reasons Data Science
Projects Fail 13. Surrounded by Success 14. O.R. in 2048 Conclusion
Appendix