The Enterprise Data Catalog
In this Early Release from O’Reilly, Ole Olesen-Bagneux explores how enterprise data catalogs are evolving in the age of AI.
For decades, search engines transformed how people discovered information on the web. Today, AI is transforming how organizations search and use enterprise data. Data catalogs are no longer just systems for discovery and governance. They now provide essential metadata and semantic context for modern AI systems.
Drawing on data management and library & information science, this book explores how metadata, enterprise ontologies, knowledge graphs, lineage, and governance help organizations improve enterprise search, data discovery, and AI explainability.
AI changes how enterprise data is searched and understood.
Traditional enterprise search focused on locating datasets, documents, and dashboards. AI systems introduce a different challenge: they require contextual understanding.
Large language models and AI systems depend on metadata, governance, lineage, and ontologies to retrieve and interpret information accurately.
This book explores how modern data catalogs are evolving into semantic systems that support both human discovery and AI-driven retrieval. Rather than treating metadata as passive documentation, The Enterprise Data Catalog, 2nd Edition shows how metadata becomes active context for AI systems and enterprise-wide search.
This Early Release edition is brought to you by Actian
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About the Book
Most organizations still approach data catalogs primarily as tools for search, governance, or compliance. But AI systems introduce a different challenge: they require contextual understanding.
This book explores how metadata, ontologies, knowledge graphs, lineage, governance, and semantic architectures help enterprises improve AI explainability, discovery, precision, and trust. It also examines how modern standards and approaches are reshaping how AI systems interact with enterprise data.
Rather than focusing on a single vendor or technology stack, the book is technology agnostic and presents practical architectural patterns and principles for building scalable metadata and governance architectures for AI.
“The data catalog is no longer just a system for finding data — it is becoming a source of context for AI.”
— Ole Olesen-Bagneux
VP, Chief Evangelist, Actian
What’s Inside
Early Release Chapters
Preface
Chapter 1: Introduction to Data Catalogs
Chapter 2: Organize Data: Design a Robust Architecture for Search
Chapter 3: Search Data: Concepts, Features, Mechanics, Patterns
Chapter 4: Search for Data Patterns
Additional chapters will be released progressively through O’Reilly Early Release.
Coming Next
Chapter 5: Access and Observe Data
Chapter 6: Empower End Users and Engage Stakeholders
Chapter 7: Data Domains
Chapter 8: Data Architecture, Providers, and Consumers
Chapter 9: Data Products and Data Contracts
Chapter 10: Manage Data: Improve Lifecycle Management
Chapter 11: The Data Catalog Is Now a Source in Itself
Chapter 12: The LLM + KG Pattern
Chapter 13: Standards and AI
What You’ll Learn
✔️ How metadata provides context for AI systems
✔️ How modern data catalogs support discovery, governance, and AI use cases
✔️ Why knowledge graphs and ontologies improve AI context and explainability
✔️ How lineage, observability, and governance support trustworthy AI systems
✔️ How MCP and agentic architectures interact with enterprise metadata
✔️ Why AI systems require semantic business context, not just raw data access
✔️ How organizations can leverage data catalog knowledge graphs for AI use cases
Who Should Read This Book?
- Data engineers
- Data scientists & data analysts
- Data management & governance professionals
- Chief Data Officers (CDOs)
- Chief Data & Artificial Intelligence Officers (CDAIOs)
- Chief Information Security Officers (CISOs)
- Data Protection Officers (DPOs)
About the Author
Ole Olesen-Bagneux
VP, Chief Evangelist, Actian
Ole Olesen-Bagneux is a globally recognized thought leader in metadata management and enterprise data architecture. As VP, Chief Evangelist at Actian, he drives industry awareness and adoption of modern approaches to data intelligence, enterprise search, and governance.
An accomplished author, Ole has written The Enterprise Data Catalog (O’Reilly, 2023). He recently published Fundamentals of Metadata Management (O’Reilly, 2025), introducing a novel metadata architecture known as the Meta Grid. With a PhD in Library and Information Science from the University of Copenhagen, he brings a unique perspective that bridges traditional information science and modern data management.
His industry experience includes leadership roles in enterprise architecture and data strategy at major pharmaceutical companies, such as Novo Nordisk. Ole is passionate about scalable metadata architectures, knowledge graphs, and enabling organizations to make data truly discoverable and usable.
