Data Governance for AI

"Data Governance for AI" is a comprehensive textbook and practical guide designed for university students and aspiring professionals. It systematically addresses the critical discipline of governing data assets for the successful and responsible development of Artificial Intelligence systems.


Philosophy

The core philosophy of this book is that effective data governance is an enabler, not a constraint, for innovation in AI. We treat data governance not as a bureaucratic overhead but as a strategic imperative that builds trust, mitigates risk, and directly enhances the performance and reliability of AI models. The text is built on the premise that a practical, hands-on understanding of governance principles is as important for an AI practitioner as understanding algorithms. It seeks to empower readers to build AI that is not just powerful, but also safe, ethical, and compliant.


Key Features

1. Globally Relevant: The content covers universally accepted frameworks, standards (like GDPR), and technologies, ensuring its applicability for students in international universities and professionals working in global organizations.
2. Beginner to Advanced Trajectory: The book caters to students with no prior knowledge of data governance while also providing in-depth material on advanced topics for senior-level undergraduates, postgraduate students, and practitioners.
3. Complete Capstone Project: The final chapter provides a complete, working DIY project with fully explained source code, allowing students to build a portfolio-worthy application.
4. Clarity and Simplicity: Complex topics are broken down into simple, easy-to-understand sections with clear explanations and relevant examples to ensure maximum comprehension.


To Whom This Book Is For


1. B.Tech/M.Tech Computer Science & Engineering Students: As a core or elective textbook that aligns with modern AI and data science curricula.
2. Aspiring Data Scientists, AI/ML Engineers, and Data Engineers: As a practical guide to mastering a critical skill set required in the industry.
3. IT Professionals and Data Analysts: For those looking to upskill and understand the governance requirements of modern AI/ML projects.
4. Technology Managers and Business Leaders: To gain a clear understanding of the strategic importance of data governance in leveraging AI for business growth.