In complex data pipelines, monitoring data lineage is crucial for ensuring data quality, regulatory compliance, and effectively troubleshooting issues. Data lineage provides a detailed map of data flows and transformations across various stages, enabling organizations to trace errors back to their upstream sources and assess their downstream impacts. Workflow orchestration tools such as Apache Airflow play a significant role in gathering lineage metadata, which helps in identifying root causes of errors, evaluating business impacts, and validating data quality with column-level precision. By utilizing lineage information, organizations can quickly address issues, maintain compliance, and ensure accurate data usage across different applications. Datadog Data Observability offers enhanced monitoring capabilities by integrating OpenLineage, allowing users to efficiently manage and resolve data pipeline errors, thereby improving their overall data governance strategy.