Nonlinear Big Data and AI-Enabled Problem-Solving
CRC Press (Verlag)
978-1-041-08696-3 (ISBN)
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This book offers a detailed insight into various business models that can be easily implemented using cutting-edge AI tools like Copilot, ChatGPT, and others. The focus is not on creating technical models for developers, but on equipping management with the necessary tools to define the scope of work and tasks for the technical team efficiently.
Nonlinear Big Data and AI-Enabled Problem-Solving: Transforming from a Spreadsheet Society provides access to a unique AI Body of Knowledge, offering actionable protocols aimed at delivering tangible and measurable economic benefits to organizations. It introduces innovative business models that can be easily implemented using cutting-edge AI tools. It provides comprehensive insights and customizable templates to help users efficiently harness the power of AI, eliminating the need for costly external assistance. This approach offers a transformative approach for traditional critical infrastructure sector organizations seeking to evolve into lean, AI-driven high-performance firms of the future.
Provides executives, senior management, and global governments with the ability to explore and achieve tangible value in solving complex and challenging problems that have previously lacked practical and effective solutions.
Dr. Scott M. Shemwell is the Managing Director of The Rapid Response Institute, USA, and is an authority and thought leader in field operations and risk management, with over 35 years in the energy sector, leading turnaround and transformation processes for global S&P 500 organizations as well as start-up and professional service firms. He has been directly involved in over $5 billion in acquisitions and divestitures, as well as the management of significant global projects and multiple business units. Dr. Shemwell has been a leader in the use of data and information enabling Operational Excellence for over 35 years. He holds a Bachelor of Science in Physics from North Georgia College, a Master of Business Administration from Houston Baptist University, and a Doctor of Business Administration from Nova Southeastern University.
1. Introduction. 2. Why Did the Data Deceive Me? 3. AI Implementation Framework. 4. Risk Mitigation and Enterprise Alignment. 5. Organization AI Culture Persona. 6. Capstone—Detailed AI Models Under Development. 7. Conclusion and Way Forward. Appendix I: Glossary of Terms. Appendix II: Variable Types. Appendix III: Major AI Resources.
| Erscheint lt. Verlag | 8.4.2026 |
|---|---|
| Zusatzinfo | 11 Tables, black and white; 26 Line drawings, black and white; 26 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Technik | |
| Wirtschaft ► Betriebswirtschaft / Management ► Logistik / Produktion | |
| ISBN-10 | 1-041-08696-2 / 1041086962 |
| ISBN-13 | 978-1-041-08696-3 / 9781041086963 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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