Assert transformations validate data quality within a pipeline. They check conditions (e.g., no nulls, value ranges, referential integrity) and fail the pipeline if violated. Used in: dbt (schema and data tests), Great Expectations, custom Spark/Python checks. Example—dbt: tests: - unique: user_id - not_null: email. In Spark: df.filter("amount < 0").count() and assert == 0....
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