This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice. It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies.

Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge.

In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.

本书是一本关于在实践中从企业关系数据库中设计和构建知识图谱的指南。它提出了一个以映射模式为中心的原则性框架，以连接关系数据库和知识图谱、组织内负责知识图谱的角色以及结合数据和人的过程。本书的内容适用于正在用属性图或RDF图技术构建的知识图。

知识图谱正在实现创建大规模整合知识和数据的智能系统的愿景。科技巨头们已经采用知识图谱作为下一代企业数据和元数据管理、搜索、推荐、分析、智能代理等的基础。我们现在观察到，越来越多的企业寻求采用知识图谱来发展竞争优势。

为了让企业设计和构建知识图谱，他们需要了解存储在关系型数据库中的关键数据。企业如何才能成功地采用知识图谱来整合数据和知识，而不至于煮沸大海？本书提供了答案。