Part II: Building Knowledge Graphs from Structured Data Sources
The journey from disparate data sources to a unified, meaningful knowledge graph represents one of the most critical challenges organizations face when implementing knowledge graph solutions. This part addresses the complex but essential process of constructing knowledge graphs from structured data sources, a fundamental step before enriching them with unstructured information and combining them with Large Language Models.
Organizations across domains typically maintain vast repositories of data, each with its own schema, structure, and storage format. The challenge lies not just in importing this data, but in harmonizing it into a coherent knowledge graph while preserving its semantic meaning and relationships. This part guides readers through this intricate process, demonstrating how to transform diverse data sources into a unified knowledge representation that serves as the foundation for more advanced applications.