metadata

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Metadata is information that describes other data. In the context of data analytics and engineering, metadata provides context about datasets, including details like column names, data types, creation dates, update frequencies, and data lineage. It's crucial for data governance, discovery, and understanding the structure and meaning of data assets. Tools like Amundsen and DataHub help organizations manage and explore metadata at scale. For example, in a DuckDB table, metadata might include the schema definition, table constraints, and column statistics. You can query metadata in DuckDB using system tables and functions like:

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-- View table metadata DESCRIBE mytable; -- Get column statistics SELECT * FROM pragma_table_info('mytable'); -- View system-wide metadata SELECT * FROM duckdb_tables();

Effective metadata management is essential for maintaining data quality, ensuring compliance, and enabling efficient data discovery and analysis across an organization.