The Fundamentals of Data Lineage in Databricks

Photo by Carlos Muza on Unsplash

In this article, we will understand data lineage in databricks a brief overview of what data lineage is and the importance of data lineage in modern data platforms. How Databricks incorporates data lineage to enhance data governance.

Types of Data Lineage in Databricks

• Technical Lineage: Table schemas, transformations, dependencies.
• Business Lineage: High-level understanding for stakeholders.

Benefits:

• Improves data quality.
• Simplifies root cause analysis.
• Enhances regulatory compliance (e.g., GDPR, HIPAA).

Data Lineage Features in Databricks

Unity Catalog Integration

• Describe Unity Catalog’s role in maintaining data lineage.
• Examples: Column-level lineage, notebook transformations, SQL queries.

Built-in Lineage Visualization

• Features: Interactive lineage graphs.
• Use case: Identifying data dependencies or impacted downstream systems.

Lineage for Notebooks

• Explain how Databricks tracks notebook execution as part of the lineage.