The Enterprise Data Catalog Scale AI with Metadata Using LLMs, MCP, and Agentic Architecture (Early Release) (Ole Olesen-Bagneux) (z-library.sk, 1lib.sk, z-lib.sk)

Author： Ole Olesen-Bagneux

It's a new day in search. Before ChatGPT, combing the web was simple—powerful search engines dominated for 25 years. That changed with conversational search powered by chatbots. Data catalogs, the search engines for your company's data, have evolved as well. The Enterprise Data Catalog explores how AI is transforming enterprise-wide data search. In this second edition, you'll explore how the role of the data catalog has changed in the age of AI. Data catalogs no longer serve as tools to find and use data—they now deliver essential metadata for AI projects. Author Ole Olesen-Bagneux explains how metadata organized as enterprise ontologies, delivered through knowledge graphs, provides the context required by large language models, Model Context Protocol, and Agent2Agent Protocol. By drawing on data management and library and information science, the book shows why information science methodology is critical to successful catalog implementations. • Understand the role of the enterprise data catalog in discovery, governance, and AI • Organize data and sources using metadata, domains, and enterprise ontologies • Search and browse data across domains, lineage, and graphs • Leverage data catalog knowledge graphs for AI use cases • Apply data catalogs to data products and data contracts