data-provenance

Track table- and column-level lineage across ETL pipelines.

11|1|Updated Jan 16, 2026

Search Tags:#compliance #ETL #metadata #data lineage #audit trail #data governance #data provenance

Ready to run

npx skills add https://github.com/sunnypatneedi/claude-starter-kit --skill data-provenance

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-provenance
Source: https://github.com/sunnypatneedi/claude-starter-kit/tree/main/skills/engineering/data-provenance
Command: npx skills add https://github.com/sunnypatneedi/claude-starter-kit --skill data-provenance

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables teams to trace the complete history and lineage of data from source to consumption, supporting trust, debugging, and compliance efforts.

Core Features & Use Cases

Table-level and column-level lineage: identify upstream sources and downstream consumers.
Audit trails and compliance: track changes for GDPR, SOX, and data governance.
Impact analysis: assess downstream effects of changes in source data.
Data catalog integration: connect lineage with a metadata catalog and queries.

Quick Start

Use the skill by enabling provenance tracking in your ETL, then run a lineage query like "What downstream tables use orders.amount?" and inspect the results in your data catalog.

Frequently Asked Questions about data-provenance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I trace data lineage from source to consumption in ETL pipelines?▼

Trace data lineage by enabling provenance tracking in your ETL pipelines, which captures table, column, row, and value-level dependencies to reveal upstream sources and downstream consumers.

What is data provenance and when do I need it for compliance auditing?▼

Data provenance is the historical record of data flow from origin to consumption. You need it for compliance auditing to track changes and ensure regulatory adherence for frameworks like GDPR and SOX.

Can I perform impact analysis on downstream tables using data lineage metadata?▼

Yes, impact analysis uses data lineage metadata to assess downstream effects. By querying lineage, you can identify exactly which downstream tables or columns are affected by changes in source data.

How do I debug data quality issues using column-level lineage?▼

Debug data quality issues using column-level lineage to trace errors back to their root source. This granular tracking pinpoints where bad data entered the ETL pipeline and why the anomaly occurred.

Does data provenance tracking integrate with an existing data catalog?▼

Yes, data provenance tracking integrates with a data catalog. You can connect lineage metadata with your catalog to query dependencies and inspect data flow results directly within your catalog environment.