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Record Nr. |
UNINA9911028754903321 |
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Autore |
Jeffery Steve |
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Titolo |
The Low-Code AI Maturity Model : Leading Responsible AI Transformation with Microsoft Power Platform |
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Pubbl/distr/stampa |
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Berkeley, CA : , : Apress L. P., , 2025 |
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©2025 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (433 pages) |
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Collana |
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Professional and Applied Computing Series |
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Disciplina |
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Soggetti |
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Business - Data processing |
Business intelligence |
Artificial intelligence - Business applications |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Part 1: Leadership and Culture -- Chapter 1: Foundational: Leadership and Culture -- Chapter 2: Emerging: Leadership and Culture -- Chapter 3: Operationalized: Leadership and culture -- Chapter 4: Integrated Excellence: Leadership and Culture -- Part 2: Establishing Trust and Governance -- Chapter 5: Foundational: EstablishingTrust and Governance -- Chapter 6: Emerging: Establishing Trust and Governance -- Chapter 7: Operationalized: Establishing Trust and Governance -- Chapter 8: Integrated Excellence:Establishing Trust and Governance -- Part 3: Data Readiness and Security -- Chapter 9: Foundational: Data Readiness and Security -- Chapter 10: Emerging: Data Readiness and Security- Chapter 11: Data Readiness and Security: Operationalized Stage -- Chapter 12: Data Readiness and Security: Integrated Excellence Stage -- Chapter 13: The Journey Forward: Leadership in the Age of Low-Code AI. |
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Sommario/riassunto |
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Written from the perspective of an experienced IT expert, this book leverages a maturity model framework to guide organizations through each stage of adopting, securing, scaling, and tracking the value of low-code AI responsibly and efficiently. |
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