Introduction to Graph Databases and Neo4j

Traditional relational databases often struggle when managing complex, highly connected data networks. This text-based course introduces you to the power of graph databases, showing you how to represent real-world entities and their relationships naturally and efficiently. You will transition from understanding basic data models to querying connected datasets with confidence. Through clear written explanations and practical query examples, you will learn how to think in graphs and solve complex data connection problems. What you'll learn: - Understand the core concepts of graph theory, nodes, relationships, and properties - Map real-world networks like social connections, recommendation engines, and organizational hierarchies - Write Cypher queries to create, read, update, and delete graph data - Compare graph database structures with traditional relational tables and document stores - Apply best practices for node labeling, relationship typing, and property indexing - Explore modern graph use cases including knowledge graphs and identity resolution This course begins with foundational definitions and key terminology before guiding you through hands-on query patterns. You will read through practical modeling scenarios, analyzing how data flows through connected nodes. Designed entirely for beginners, this course requires no prior database experience or mathematical background. Start reading today to unlock the potential of connected data.