Data engineering doesn't have to be slow or code-heavy. Learn how AI, no-code automation, and Data Vault turn metadata into production-ready platforms, enabling small teams to deliver analytics and AI at enterprise scale
Key Features
- Accelerate Data Vault platforms with AI and no-code automation using Flow.BI and Datavault Builder
- Streamline modeling, generation, analytics, and operations with dbt and metadata-driven automation
- Enable business users to query governed data using semantic layers and AI-powered access
Book Description
Modern data platforms must be faster, scalable, and intelligent; however, traditional data engineering approaches are often slow, manual, and difficult to scale. Building Autonomous Data Platforms with AI introduces a new paradigm where artificial intelligence, metadata-driven automation, and modern architectures work together to simplify and accelerate data platform development. This book provides a practical, end-to-end guide to designing and implementing autonomous data platforms using proven approaches such as Data Vault, layered architectures, and AI-assisted modeling. You will learn how to automate data integration, generate scalable data models, and deliver trusted, analytics-ready data products with minimal manual effort. Through real-world tools and frameworks such as Flow.BI, Datavault Builder, and dbt, the book demonstrates how to move from conceptual models to fully operational data platforms. You will also learn governance, performance optimization, lineage, and observability to ensure long-term reliability. With dedicated coverage of semantic layers and agentic AI, you will discover how to enable natural language access to data while maintaining accuracy and trust. By the end of this book, you will be able to build intelligent, automated data platforms that deliver trusted analytics and AI at scale.
What you will learn
- Understand autonomous data platforms, Data Vault, and modern data architectures
- Apply AI-driven, metadata-driven modeling to design scalable data platforms
- Automate Raw and Business Vault generation using no-code tools
- Use Flow.BI, Datavault Builder, and dbt in real-world data workflows
- Build analytics-ready access layers and semantic models
- Enable governed, natural language data access with AI
- Implement governance, lineage, and operate production-ready platforms with small teams
Who this book is for
This book is ideal for data architects, data engineers, analytics engineers, and platform teams looking to modernize their data landscape, reduce complexity, and build future-ready data platforms that scale with evolving business demands and AI-driven innovation. A basic understanding of data warehousing concepts will help you get the most from this book, while both code-focused and no-code practitioners will benefit from its practical, hands-on guidance.
