From Air Quality to Aircraft and Automobiles, Data Is Everywhere
summary
Shows a runnable pattern that wires Apache NiFi, Snowflake, Neo4j, Cortex AI and local LLMs like LLAMA into a RAG pipeline for an open lakehouse using Iceberg or native Snowflake tables and Snowpark so graph algorithms execute where the data lives without copying it. Includes code and a Streamlit ghost‑hunting demo that combines Neo4j in Snowflake Marketplace, autotested SQL procedures, graph embeddings and Cortex AI connectors; demo runs but UI graph integration is still being finished and all code is on GitHub.
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chapters (6)
- 0:00Introduction and setup
- 1:10Graph AI integration overview
- 3:20Snowflake marketplace demo
- 7:20Neo4j integration steps
- 9:29Ghost hunting application
- 12:22Q&A and resources
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