Tutorial Shows How to Automate Data Pipeline Dependency Tracking with DataLineage

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A developer tutorial published on DEV Community demonstrates how to use the DataLineage API to automatically trace and manage dependencies across mixed data pipelines. The guide targets data engineers who face cascading failures when upstream schema changes break downstream dashboards or jobs without warning. It walks through building a Python API client that connects to three key endpoints for tracing dependencies, retrieving lineage graphs, and simulating the impact of proposed changes. The tutorial covers pipelines combining dbt, Apache Airflow, and custom ETL processes, storing a queryable lineage graph for ongoing use. The core goal is to enable teams to run impact analysis before a schema change is deployed, rather than diagnosing breakages after the fact.

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