Amundsen

About Amundsen

Data discovery and metadata engine for improving productivity of data analysts, scientists, and engineers when interacting with data. Provides powerful search, data previews, and column-level lineage. Integrates seamlessly with Python environments and modern data stacks for comprehensive metadata management.

Key Features

• 1Data discovery search engine built on metadata from multiple sources
• 2Automated table popularity ranking based on query frequency
• 3Data lineage graph connecting datasets across tools and systems
• 4Metadata ingestion connectors for BigQuery, Redshift, Snowflake, and more
• 5Python-based databuilder framework for custom metadata extraction

How Python Data Engineers Use Amundsen

Python data engineers use Amundsen's databuilder library to write custom extractor jobs that pull metadata from internal databases and push it to Amundsen's index. Engineers also use the Amundsen API to programmatically tag datasets with ownership, freshness SLAs, and quality tier labels that the search UI surfaces to data consumers.