Fr. 52.50

Precisely - Working With Precision Systems in a World of Data

Inglese · Copertina rigida

Spedizione di solito entro 1 a 3 settimane (non disponibile a breve termine)

Descrizione

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Precisely provides a blueprint for how professionals in the private and public sectors can use big data with precision systems, the highly engineered working arrangements of people, processes, and machines powered by artificial intelligence and machine learning.

Sommario

Foreword, by Thomas H. Davenport
1. Introduction: From Digitization to Precision
2. Six Kinds of Precision Systems
3. Design, Test, and Prove: Key Steps in Building a Precision System
4. Getting Started with Data and Platforms
5. The Precision Vanguard
6. The Political Management of Precision
7. Bootstrapping Precision
8. Creating and Managing Teams of Precision
9. Building the Precision Enterprise
10. Red Zones of Precision
11. Summing Up: Some Final Lessons for Leaders
Acknowledgments
Chapter Notes
Bibliography
Index

Info autore

Zachary Tumin is a member of the faculty at Columbia University’s School of International and Public Affairs. He has served in senior executive positions in public administration, industry, and academia, from Harvard Kennedy School to Wall Street’s Financial Services Technology Consortium to New York City government. With William Bratton, Tumin is coauthor of Collaborate or Perish! Reaching Across Boundaries in a Networked World (2012).

Madeleine Want is vice president of data at Fanatics Betting and Gaming. Her previous roles include product management for data at Audible and Axel Springer.

Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, the cofounder of the International Institute for Analytics, a fellow of the MIT Initiative for the Digital Economy, and a senior advisor to Deloitte Analytics.

Riassunto

Precisely provides a blueprint for how professionals in the private and public sectors can use big data with precision systems, the highly engineered working arrangements of people, processes, and machines powered by artificial intelligence and machine learning.

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