Integrating Metadata Lineage into Data Quality and Monitoring

How to connect data validation rules directly to conceptual, logical, and physical models

Summary

In the previous article, we visualized metadata lineage across conceptual, logical, and physical models — revealing how data flows through the system.

Now, we’ll take that lineage one step further and make it actionable: using it to drive data quality checks and monitoring logic.

When your quality rules are connected to metadata lineage, you can test data integrity automatically — in the right place, at the right layer, with full traceability back to the business meaning.

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1. From Modeling to Monitoring

Traditional data quality checks often live in isolation — in SQL scripts, ETL jobs, or dashboards. In a metadata-driven architecture, those rules become metadata themselves: documented, traceable, and linked to the entities and attributes they protect.

With lineage in place, you can answer:

• “Which data quality checks cover this business concept?”
• “What percentage of logical attributes are validated?”