Build Auto Lineage

Data Lineage tracks data from its source to its destination, tracing it through transformations, steps, and usages. It visualizes data flow, helping with data integrity, regulatory compliance, data quality improvement, and effective data management.

Data lineage is crucial for several reasons:

• Data Quality: It shows where data comes from and how it changes. Understanding the lineage helps identify and fix data quality issues.

• Compliance and Governance: Data lineage shows how data is handled and where it is used. It helps organizations meet regulatory compliance requirements and demonstrate data provenance.

• Impact Analysis: Data lineage shows the impact of changes to data sources or transformations on downstream processes and applications.

• Troubleshooting: Data lineage helps trace the origin of data issues or errors and speeds up resolution.

• Data Understanding: Clear data lineage helps analysts, scientists, and business users understand the data and its relationships.

Data lineage often appears in visual diagrams, showing the data's path from source to destination with steps and transformations. These diagrams are part of a larger data governance framework and are valuable for organizations handling sensitive or regulated data.

Lineage is built using the Views, Stored Procedures, Functions, Triggers, Package Body, Source Code of ETL and Reporting databases, and Files (JSON, XML, yaml, .csv, and .config files).

There are two methods for building lineage within the application:

1. Manual Lineage: This process builds lineage manually using

   1. Lineage Maintenance

   2. Load Metadata from Files

   3. Advanced Jobs

   4. API’s

2. Auto Lineage: This process creates lineage automatically using

   1. Parsing queries or Source codes using Build Auto Lineage

   2. Advanced Jobs

---

Copyright © 2025, OvalEdge LLC, Peachtree Corners, GA, USA.