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A team of data engineer are adding tables to a DLT pipeline that contain repetitive expectations for many of the same data quality checks. One member of the team suggests reusing these data quality rules across all tables defined for this pipeline. What approach would allow them to do this?
Correct Answer: A
Maintaining data quality rules in a centralized Delta table allows for the reuse of these rules across multiple DLT (Delta Live Tables) pipelines. By storing these rules outside the pipeline's target schema and referencing the schema name as a pipeline parameter, the team can apply the same set of data quality checks to different tables within the pipeline. This approach ensures consistency in data quality validations and reduces redundancy in code by not having to replicate the same rules in each DLT notebook or file. References: * Databricks Documentation on Delta Live Tables: Delta Live Tables Guide
