Open Source · Built for Microsoft Fabric

Visualize Data Dependencies

in Fabric Warehouses

Trace how data flows through stored procedures, views, and functions. Understand object dependencies at a glance. Built natively for Microsoft Fabric.

View on GitHub Watch Demo Quick Start
Fabric native lineage - item-level view

The Problem

Data warehouses grow complex. Dependencies hide in SQL code. Impact analysis becomes guesswork.

Hidden Dependencies

Stored procedures call other procedures. Views reference tables across schemas. The full picture is scattered across hundreds of objects.

Risky Changes

Renaming a table? Modifying a view? You need to know every SP, report, and downstream process that depends on it.

Slow Onboarding

New team members spend weeks understanding data flow. Documentation is outdated. Tribal knowledge is the only guide.

The Solution

Interactive object-level lineage visualization

Fabric Data Lineage - Interactive dependency graph visualization

Features

Interactive visualization for understanding object-level data lineage

Interactive Graph

Pan, zoom, and explore. Nodes color-coded by schema. Click any object to highlight its connections. Supports hundreds of objects.

Trace Mode

Right-click any object to trace upstream sources or downstream consumers. Configurable depth from 1 to unlimited levels.

Search & Filter

Full-text search across all SQL definitions with syntax highlighting. Filter by schema, object type, or data model classification — with automatic neighbor inclusion.

Multi-Warehouse

Connect multiple Fabric Data Warehouses. Switch between sources with a dropdown. External references (other DBs, Azure Storage) are tracked.

Export

Export the current view as PNG, JPEG, or Draw.io diagram. Draw.io export preserves schema colors and includes the legend — ready to edit in Diagrams.net.

Graph Analysis

Structural analysis in one click. Detect Islands (disconnected subgraphs), Hubs (high-degree nodes), Orphans, Longest dependency chains, and Cycles. Results highlight directly in the graph.

See It In Action

Data Lineage Demo Video

Click to watch: Full walkthrough of trace mode, schema filtering, and interactive features

What's Included

Clear scope and honest limitations

Supported

  • ✓ Tables, Views, SPs, Functions
  • ✓ Multiple warehouses
  • ✓ External references (cross-database, Storage, OneLake)
  • ✓ Metadata only, no table data
  • ✓ Stays in your tenant

Current Scope

  • Object-level lineage (column-level not included)
  • Fabric Data Warehouse only
  • Dynamic SQL via hardcoded hints

How It Works

Three steps, all within your Fabric workspace

1
Connect Point to your Fabric Data Warehouse — only metadata is read, never your actual data
2
Discover Dependencies are automatically detected from your SQL definitions
3
Explore Visualize and trace data flow — everything stays secure in your tenant
Architecture diagram

Quick Start

Try it in minutes with Demo Mode

1

Admin Setup

Enable workloads and deploy your own package — see quick start and Microsoft deployment guide

2

Try Demo

+ New → Data Lineage → Refresh
(demo mode is default)

3

Your Warehouse

Connect your data via setup guide

Full Quick Start Guide →

Want to explore lineage quickly?

Check out the VS Code extension — visualize object dependencies and data lineage from .dacpac files or by importing directly from SQL Server, Azure SQL, Fabric DW, and Synapse databases. No Fabric tenant required.

View on Marketplace →
Christian Wagner

Christian Wagner

Data Architect & Engineer

Building tools to make data engineering workflows more transparent and efficient. Focused on the Microsoft data stack, cloud architecture, and developer experience.