AI-Ready Data
Autor Andrew Madsonen Limba Engleză Paperback – 19 oct 2026
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Specificații
Notă biografică
ANDREW MADSON is a member of the technical staff at Perplexity AI, where he leads global developer relations. A veteran data strategy leader, Madson has shaped data infrastructure at Fortune 100 organizations including JPMorganChase and MassMutual, as well as high-growth startups like Dremio. He is a regular keynote speaker at industry conferences and reaches hundreds of thousands of data professionals through his blog, podcast, and newsletter.
Cuprins
Author Bio xviii
Acknowledgments xix
Introduction xx
Chapter 1: Model Access Is Becoming a Commodity, and Data Is a Durable Advantage 1
Chapter 2: The Data-AI Gap 17
Chapter 3: Mapping Your Data for AI 29
Chapter 4: The CRAFT Assessment Framework 45
Chapter 5: CRAFT, Ethics, Privacy, and Compliance 66
Chapter 6: Framework Summary 85
Chapter 7: Raw Data and CRAFT 95
Chapter 8: Systems for Raw Data 112
Chapter 9: Structured Data and CRAFT 126
Chapter 10: Systems for Structured Data 151
Chapter 11: Context Data and CRAFT 168
Chapter 12: Systems for Context Data 186
Chapter 13: Action Data and CRAFT 204
Chapter 14: Systems for Action Data 224
Chapter 15: Assessing and Measuring CRAFT 237
Chapter 16: Organizing for CRAFT 256
Chapter 17: Governance for AI-ready Data 268
Chapter 18: The Economics of CRAFT 283
Chapter 19: Quick Wins and the 90-day Plan 298
Chapter 20: The Last Mile Is Technical and Human 314
Chapter 21: Conclusion: Models Converge. Data Differentiates 324
References 329
Appendix A CRAFT Assessment Matrix 330
Appendix B When Culture Breaks Data Loops 332
Appendix C Entity Integrity 334
Index 336
Acknowledgments xix
Introduction xx
Chapter 1: Model Access Is Becoming a Commodity, and Data Is a Durable Advantage 1
Chapter 2: The Data-AI Gap 17
Chapter 3: Mapping Your Data for AI 29
Chapter 4: The CRAFT Assessment Framework 45
Chapter 5: CRAFT, Ethics, Privacy, and Compliance 66
Chapter 6: Framework Summary 85
Chapter 7: Raw Data and CRAFT 95
Chapter 8: Systems for Raw Data 112
Chapter 9: Structured Data and CRAFT 126
Chapter 10: Systems for Structured Data 151
Chapter 11: Context Data and CRAFT 168
Chapter 12: Systems for Context Data 186
Chapter 13: Action Data and CRAFT 204
Chapter 14: Systems for Action Data 224
Chapter 15: Assessing and Measuring CRAFT 237
Chapter 16: Organizing for CRAFT 256
Chapter 17: Governance for AI-ready Data 268
Chapter 18: The Economics of CRAFT 283
Chapter 19: Quick Wins and the 90-day Plan 298
Chapter 20: The Last Mile Is Technical and Human 314
Chapter 21: Conclusion: Models Converge. Data Differentiates 324
References 329
Appendix A CRAFT Assessment Matrix 330
Appendix B When Culture Breaks Data Loops 332
Appendix C Entity Integrity 334
Index 336