What is metadata in a data pipeline?
💡 Model Answer
Metadata in a data pipeline refers to descriptive information about the data that flows through the pipeline. It includes details such as data source, schema, lineage, transformation logic, timestamps, quality metrics, and ownership. Metadata enables monitoring, debugging, and governance by providing context about where data came from, how it was processed, and where it is stored. For example, a pipeline might record that a CSV file from an FTP server was ingested, transformed by a Spark job that added a calculated column, and loaded into a Snowflake table. This metadata can be stored in a catalog or metadata store, allowing users to query lineage, audit changes, and enforce data quality rules.
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