Overview

A comprehensive and detailed guide for business and technology leaders ready to implement AI throughout their organizations A soup to nuts strategy guide for business leaders interested in implementing artificial intelligence in their organizations in a way that drives real-world results, Data Makes the World Go ‘Round: The Data, Tech, and Trust Behind AI Success combines specific, actionable advice for technical and business leaders on issues like data management, data architectures, AI tools, AI operationalization, and AI governance. Veteran technology and business analyst, researcher, and leader, Fern Halper, walks you through the organizational and technical factors that determine success in data, analytics, and AI. This book brings together the insights, case studies, and leader interviews that set out exactly what you need to succeed as you incorporate artificial intelligence throughout your organization. It covers the latest trends in data and AI (and how they’re relevant to your top- and bottom-lines), data products, data fabric, and AI responsibility, risk mitigation, and ethics. Inside the book: Specific steps to building the robust internal data foundation you’ll need for artificial intelligence implementation How to democratize business intelligence so data analysts are free to conduct deeper analyses and perform more sophisticated analytical roles Informed advice for building AI models, applications, and innovations, and explanations of best practices for model building aligned with your organization’s strategies Perfect for business and technology leaders working towards a comprehensive data and AI strategy, Data Makes the World Go ‘Round: The Data, Tech, and Trust Behind AI Success is a deeply informed, up-to-date, and practical exploration of the foundations of every successful AI transformation – and how you can build them in your own organization.

Full Product Details

Author:   Fern Halper
Publisher:   John Wiley & Sons Inc
Imprint:   John Wiley & Sons Inc
Dimensions:   Width: 18.50cm , Height: 1.50cm , Length: 23.10cm
Weight:   0.635kg
ISBN:  

9781394390632

ISBN 10:   1394390637
Pages:   320
Publication Date:   24 March 2026
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Awaiting stock  

Table of Contents

Acknowledgments xiii About the Author xv Introduction 1 Part I The AI Imperative 7 Chapter 1 The Business Case for Analytics and Artificial Intelligence 9 Chapter 2 The Leadership Challenge 21 Chapter 3 The AI Journey 35 Part II Building the Data Foundation for AI 45 Chapter 4 The New Data Landscape 47 Chapter 5 The Need for Modern Data Architectures 57 Chapter 6 Metadata: What It Is and How It Is Evolving 71 Chapter 7 The Data Quality and Data Governance Imperatives 79 Chapter 8 Data Products 87 Part III Democratizing Analytics 97 Chapter 9 The Self-service Imperative 99 Chapter 10 Artificial Intelligence in Business Intelligence 111 Chapter 11 Ensuring Data Literacy 121 Chapter 12 Putting Self-service to Work in Your Company 131 Part IV The AI Build-Out—Ecosystem, Models, Operations, and the Shift to Agents 145 Chapter 13 The Business Strategy Behind the Technology 147 Chapter 14 The AI Ecosystem 159 Chapter 15 Building AI Models 173 Chapter 16 Operationalizing AI 191 Chapter 17 Generative AI 201 Chapter 18 Agentic AI 217 Part V Governing Data and AI—Ensuring Trust and Compliance 229 Chapter 19 Data Governance—Building Trust for AI 231 Chapter 20 Analytics and AI Governance—Managing Risk and Performance 249 Part VI Putting It All Together 279 Chapter 21 Tying It All Together 281 Conclusion 292 Index 293

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Author Information

FERN HALPER, PhD, has over two decades' experience helping organizations navigate rapid innovation. As a practitioner, industry analyst, researcher, and thought leader, she has led initiatives in e-commerce, big data, cloud computing, and artificial intelligence. She is currently a leader at TDWI, a company dedicated to research and education in data management, BI, AI, and governance.

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