Enterprise Knowledge Graphs in Action

Managing siloed enterprise data across complex operational domains requires robust, interconnected architectures. This written course guides you through the principles and implementation of enterprise knowledge graphs, showing you how to turn fragmented information into an intelligent, unified semantic data network. You will develop a clear understanding of semantic data modeling, graph query languages, and ontology design tailored for data-intensive enterprise environments. What you'll learn: - Understand core graph terminology, resource description frameworks, and property graph fundamentals - Design domain ontologies and taxonomies to represent complex business relationships accurately - Query and navigate graph structures effectively using standard graph query patterns - Connect disparate relational, unstructured, and operational data sources into a centralized knowledge layer - Apply data validation mechanisms and governance frameworks to maintain graph integrity - Integrate knowledge graphs with modern retrieval-augmented generation and analytics workflows You will begin with essential terminology, basic graph concepts, and fundamental data definitions before advancing to real-world enterprise architectures, semantic modeling patterns, and integration strategies. This course is designed for data analysts, software engineers, and technology professionals who want to understand knowledge graph implementation from the ground up, with no prior graph database experience required. Start reading today to build scalable, interconnected data models for modern enterprise systems.