You'll learn to reason in nodes, edges, and relationships, and to judge when connected context better supports certain relationship-centered or variable-depth questions than tables and hierarchies do. You'll practice separating observed relationships from inferred cause and translating graph evidence into decision-ready advice without writing code or producing technical data designs.
Overview
Syllabus
- Unit 1: Core Graph Concepts
- When Rows Win and When Connections Win
- Mapping the Language of Graphs
- Explaining Connected Context to a Skeptic
- Unit 2: Entity and Relationship Meaning
- Entity Resolution Beyond Duplicate Records
- Decoding Data Identity Concepts
- Reading Identity Before Approving Merges
- Unit 3: Evaluating Graph Fit
- Identifying Use Cases and Failure Modes
- Matching Connected Use Cases to Questions
- Bounding a Sponsor's Graph Ambition
- Unit 4: Interpreting Connected Evidence
- Reading Co-Occurrence Without Naming a Culprit
- Observed, Inferred, or Just Structural?
- Separating Observed Links From Inferred Blame