Blog
Lineage and impact, in practice
Practical guides on SQL lineage, hidden pipeline dependencies, and understanding impact before you change your warehouse.
Featured · Comparison
Data lineage tools for modern warehouse teams
Compare data lineage tools for impact analysis, dependency mapping, and safer schema changes across warehouses, pipelines, and BI.
8 min readRead the article →
Comparison
OQEN vs sqllineage: when a library is enough
Compare OQEN with the open-source sqllineage and sqlglot libraries: what each does well, where a library is enough, and when impact analysis needs more.
6 min read
Fundamentals
What is data lineage tracking and why does it matter?
Learn what data lineage tracking is, how it works, and why mapping pipeline metadata matters for impact analysis, debugging, and safer schema changes.
16 min read
Pipelines
Find the SQL hidden inside your Python and Airflow pipelines
See how SQL hides inside Python files, Airflow operators, sensors, and ETL jobs, and why this matters for accurate lineage and impact analysis.
10 min read
Schema changes
What breaks before a schema change? How to check first
Learn how to check downstream dependencies, views, and database objects before schema changes so teams can avoid broken pipelines and BI reports.
9 min read
SQL parsing
Why parsing PL/SQL is hard, and how to map what it touches
Understand why SQL and PL/SQL parsing is difficult, how parse trees support lineage, and how to map tables, columns, and downstream dependencies.
8 min read