Live interview from July 9th with Mark Grover, Product Manager at Lyft. Mark is working on Lyft's data discovery and metadata engine, Amundsen, which uses Neo4j as the backend data source for data discovery.

During this 25-min session, Mark takes a deep dive into Amundsen's architecture which leverages a comprehensive Neo4j knowledge graph, centralized metadata and PageRank to achieve amazing results by reducing the time it takes to discover data by 10x!

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Blog post from Lyft describing the problem and solution (Amundsen):
https://eng.lyft.com/amundsen-lyfts-data-discovery-metadata-engine-62d27254fbb9?gi=c1730f1508dd

Open source code repo and documentation:
https://github.com/lyft/amundsenfrontendlibrary