Why Data Modeling Matters and Why It's Important to You
summary
A synthetic anti‑money‑laundering dataset loads two ways: one import creates only transaction nodes (nodes exist but no relationships), the other uses MERGE to create unique sender and beneficiary nodes and a send_money edge in Neo4j. The first query returns isolated transactions that hide repeat-sender patterns; the second produces connected graphs that let simple counts and path queries surface repeated sender→beneficiary chains and suspicious clusters, proving the relational model works for detection.
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chapters (4)
- 0:00Introduction to data modeling
- 3:59Why graphs solve real-world problems
- 9:56Live demo on graph modeling
- 15:25Key takeaways and Q&A
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