fabric-medallion

Design Bronze, Silver, and Gold Medallion pipelines in Microsoft Fabric Lakehouse using Delta Lake.

4|1|Updated May 22, 2026
One-click install
npx skills add https://github.com/ThomazRossito/ai-data-agents --skill fabric-medallion-thomazrossito
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fabric-medallion
Source: https://github.com/ThomazRossito/ai-data-agents/tree/main/plugins/ai-data-agents/skills/fabric-medallion
Command: npx skills add https://github.com/ThomazRossito/ai-data-agents --skill fabric-medallion-thomazrossito

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Designing data pipelines in Microsoft Fabric Lakehouse requires correct decisions about Delta Lake storage, layer separation, V-Order optimization, and Direct Lake compatibility — mistakes cause Power BI fallback to DirectQuery and poor performance. This Skill provides the architecture patterns, code templates, and checklists to build Medallion pipelines correctly from the start. ## Core Features & Use Cases - Layer-by-Layer Guidance: Concrete PySpark and SparkSQL patterns for Bronze ingestion (Auto Loader, metadata columns), Silver cleansing (MERGE upserts, deduplication, PII masking), and Gold star schemas (surrogate keys, OPTIMIZE, V-Order). - OneLake & Shortcuts Patterns: ABFSS path conventions, multi-schema Lakehouse creation, cross-workspace shortcuts with conflict policies, and retention policies per layer. - Direct Lake Safeguards: Rules and checklists that prevent Power BI fallback to DirectQuery, including CLUSTER BY usage, view avoidance, and small-file consolidation. - Use Case: When asked to build a sales analytics pipeline in Fabric, apply this Skill to generate the Bronze ingestion notebook with Auto Loader, the Silver MERGE logic, and the Gold fact/dimension tables ready for Direct Lake consumption. ## Quick Start Design a Medallion architecture pipeline in Microsoft Fabric Lakehouse for my orders data, including Bronze ingestion, Silver cleansing with MERGE, and a Gold star schema optimized for Direct Lake.

Frequently Asked Questions about fabric-medallion

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

FAQPage Schema
How do I implement Medallion architecture in Microsoft Fabric Lakehouse?▼

Create separate Lakehouses or schemas for Bronze, Silver, and Gold layers. Ingest raw data into Bronze with metadata columns, cleanse and deduplicate into Silver using MERGE upserts, and build star schema tables in Gold with V-Order and OPTIMIZE for Direct Lake consumption.

How to perform upserts on Delta tables in Fabric with PySpark?▼

Use the DeltaTable API merge method with whenMatchedUpdateAll and whenNotMatchedInsertAll on a key column like order_id. Read incremental Bronze data filtered by ingestion timestamp, apply Silver transformations, then execute the merge against the target Delta table.

Should I use Tables or Files in a Fabric Lakehouse?▼

Use Tables for structured data consumed by Power BI or the SQL Analytics Endpoint, since they provide ACID transactions and Direct Lake support. Use Files only for raw landing zones, archives, and reference files in any format.

Why does Power BI Direct Lake fall back to DirectQuery?▼

Fallback happens when the semantic model uses T-SQL views, tables lack V-Order, data contains complex types like arrays, or tables have too many small files. Materialize views as Delta tables, enable V-Order, flatten nested data in Silver, and run OPTIMIZE regularly.

When should I use OneLake shortcuts instead of copying data?▼

Use shortcuts when data already exists in ADLS Gen2, S3, Dataverse, or another Fabric workspace and you want zero-copy real-time access. Use Copy Activity when you need local storage, lowest query latency, or data isolated from source changes.

What retention policy should each Medallion layer have?▼

Bronze typically retains 30-90 days of raw data, Silver retains 1-2 years of cleansed data, and Gold retains 3 or more years for compliance. Enforce retention by running VACUUM with matching RETAIN HOURS values on each Delta table.