fabric-lineage

Extract lineage from Fabric artifacts using SQL connector or regex DDL parsing.

Updated May 26, 2026
One-click install
npx skills add https://github.com/rbutinar/ade-ops --skill fabric-lineage
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fabric-lineage
Source: https://github.com/rbutinar/ade-ops/tree/main/.agents/skills/fabric-lineage
Command: npx skills add https://github.com/rbutinar/ade-ops --skill fabric-lineage

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires sys.sql_expression_dependencies, regex, inventory.json, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill extracts lineage relationships from Fabric artifacts (views, stored procedures, pipelines) and persists them into a metadata catalog, enabling users to track and manage data lineage across Fabric environments.

Core Features & Use Cases

  • Lineage Extraction: Extracts lineage relationships from Fabric artifacts like views, stored procedures, and pipelines.
  • Data Catalog Integration: Persists extracted lineage into a metadata catalog for easy access and management.
  • Use Case: Ideal for organizations that require a comprehensive understanding of their data flow in Fabric environments to ensure data integrity and compliance.

Quick Start

Run the fabric-lineage skill with the target and method of your choice, for example: /fabric-lineage all native --env dev

Frequently Asked Questions about fabric-lineage

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

FAQPage Schema
How do I automate data lineage extraction from Fabric artifacts?

You can automate data lineage extraction by running the fabric-lineage skill against Fabric artifacts. It uses a Fabric Warehouse SQL connector or regex-based DDL parsing to extract relationships from views, procedures, and pipelines, then persists them into a metadata catalog.

What is Fabric data lineage extraction and why is it needed?

Fabric data lineage extraction tracks data flow relationships across views, stored procedures, and pipelines. It is needed to maintain a comprehensive metadata catalog, ensuring data integrity and compliance across Fabric environments.

Do I need an inventory JSON file to extract lineage in Fabric?

Yes, you need an inventory JSON file generated by fabric-extract-v2. You also need a connection to a Fabric Warehouse and a lineage metadata catalog to persist the extracted data flow relationships successfully.

Can I extract lineage from stored procedures and pipelines using SQL dependencies?

Yes, you can extract lineage from stored procedures and pipelines. The skill queries sys.sql_expression_dependencies within the Fabric Warehouse SQL connector to map and persist these data flow relationships automatically.

What is the best way to parse DDL for data lineage when SQL connectors are unavailable?

Regex-based DDL parsing is the alternative method for lineage extraction when native SQL connectors are unavailable. This approach parses Fabric artifacts directly to capture data flow relationships for your metadata catalog.

Are there limitations when extracting Fabric lineage across different targets?

Lineage extraction targets are limited to views, stored procedures, and pipelines. You must specify a valid target and method, such as native or regex, and ensure your Fabric Warehouse connection is active to avoid extraction failures.