Getting Started
What Is Microsoft Fabric? A Practical Overview
Understand how OneLake, workspaces, Lakehouses, Warehouses, notebooks, pipelines, SQL endpoints and semantic models fit together.
Planned · View in editorial roadmap →Guided learning path
Microsoft Fabric
Learn Microsoft Fabric by building
Start with a workspace and your first notebook, then progress through Lakehouses, Delta tables, Warehouses, Git, CI/CD and production-scale engineering.
01—12
Start Here
Follow the core path from an empty workspace to a production-ready data workflow.
- 01Workspace
- 02Lakehouse
- 03Notebook
- 04Explore data
- 05Delta tables
- 06Warehouse
- 07Pipelines
- 08Git
- 09CI/CD
- 10Logging
- 11Debugging
- 12Performance
Getting Started2 tutorials
Getting Started
Create Your First Microsoft Fabric Workspace
Create a development workspace with sensible capacity, access and ownership decisions from the start.
Planned · View in editorial roadmap →
Lakehouse & Notebooks5 tutorials
Your First Data
Create Your First Fabric Lakehouse
Build a Lakehouse and understand its Files, Tables and SQL analytics endpoint surfaces.
Planned · View in editorial roadmap →Your First Data
Create Your First Fabric Notebook
Use PySpark to load, inspect and summarize a dataset in your first Fabric notebook.
Planned · View in editorial roadmap →Play with Data
Explore Data with PySpark in Microsoft Fabric
Practice the DataFrame operations used to explore and shape data in Fabric notebooks.
Planned · View in editorial roadmap →Play with Data
Use SQL Inside a Fabric Notebook
Query notebook data with Spark SQL and decide when SQL or PySpark is the clearer tool.
Planned · View in editorial roadmap →Play with Data
Write Your First Delta Table in Fabric
Persist a DataFrame as a managed Delta table and query it from Spark and SQL.
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Medallion Architecture10 tutorials
Learn how to structure raw, conformed and serving data layers without over-engineering the platform.
Foundations
Medallion Architecture Explained: Bronze, Silver and Gold
What the Bronze, Silver and Gold layers are for, how data quality and incremental processing work across them in Microsoft Fabric, and when fewer layers are the better design.
Read tutorial →Foundations
When You Should NOT Use All Three Medallion Layers
A critical look at the Medallion pattern: when two layers or a single curated model are enough, and the cost that each unnecessary layer adds.
Planned · View in editorial roadmap →Layer design
Designing a Bronze Layer in Microsoft Fabric
How to design a Bronze layer that preserves source fidelity: landing formats, ingestion metadata, schema drift, retention and replay.
Planned · View in editorial roadmap →Layer design
Designing a Silver Layer for Clean and Conformed Data
How to turn source-shaped Bronze data into clean, validated, conformed Silver entities that several consumers can share.
Planned · View in editorial roadmap →Layer design
Designing a Gold Layer for Reporting and APIs
How to design the Gold layer that reports, semantic models and APIs consume: modelling choices, stable contracts, serving engines and how to change it without breaking consumers.
Planned · View in editorial roadmap →Engineering patterns
Incremental Processing Across Bronze, Silver and Gold
How changes propagate from Bronze to Silver to Gold without full reloads: change detection between layers, affected keys and recomputing only impacted aggregates.
Planned · View in editorial roadmap →Engineering patterns
Delta MERGE Patterns in a Medallion Architecture
Which write pattern belongs in which layer: append in Bronze, MERGE for Silver entities and history, and targeted overwrite or MERGE for Gold.
Planned · View in editorial roadmap →Engineering patterns
Partitioning Strategies Across Medallion Layers
Why the right partitioning often differs by layer, from load-date partitions in Bronze to unpartitioned Gold tables, and how to decide.
Planned · View in editorial roadmap →Engineering patterns
Small Files and Compaction in Medallion Architectures
Where small files come from in each layer and how to plan OPTIMIZE, V-Order and VACUUM per layer instead of applying one schedule everywhere.
Planned · View in editorial roadmap →Capstone
Building an End-to-End Fabric Medallion Pipeline
A complete, production-minded Medallion pipeline in Fabric: incremental ingestion, quality gates, MERGE, maintenance, logging and deployment. It builds on the first end-to-end pipeline tutorial.
Planned · View in editorial roadmap →
Warehouse1 tutorials
Lakehouse & Warehouse
Lakehouse vs Warehouse in Microsoft Fabric: How I Decide
The criteria I use to choose between a Fabric Lakehouse and a Fabric Warehouse: team skills, write patterns, T-SQL needs and governance.
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Pipelines2 tutorials
Build with Data
Build Your First End-to-End Fabric Pipeline
Move CSV or Parquet through a notebook-driven Bronze, Silver and Gold flow into a queryable serving layer.
Planned · View in editorial roadmap →Parameterized Notebooks
Make Your Fabric Notebook Reusable with Parameters
Pass dates and business identifiers from a pipeline into one reusable Fabric notebook.
Planned · View in editorial roadmap →
Git & CI/CD5 tutorials
Getting Started
Connect Microsoft Fabric to Git
Connect a Fabric workspace to a repository and understand branches, synchronization, versioned artifacts and current limitations.
Planned · View in editorial roadmap →Git & CI/CD
Git Integration in Microsoft Fabric
Use Fabric Git integration deliberately across branches, workspace artifacts and team workflows.
Planned · View in editorial roadmap →Git & CI/CD
Designing Dev, Test and Production Deployments for Fabric
How to promote Fabric items between environments: configuration per environment, data separation, approvals and rollback.
Planned · View in editorial roadmap →Git & CI/CD
CI/CD for Microsoft Fabric: A Practical Deployment Strategy
A practical deployment approach for Fabric items using Git integration, deployment pipelines and automation, including what still needs manual steps.
Planned · View in editorial roadmap →Git & CI/CD
What Actually Gets Deployed in Fabric?
Separate deployable workspace artifacts from data, connections and environment-specific configuration.
Planned · View in editorial roadmap →
Production Engineering3 tutorials
Production Engineering
Logging Your Fabric Notebooks Properly
Design an execution log that makes notebook and pipeline runs traceable in production.
Planned · View in editorial roadmap →Production Engineering
Debugging Fabric Notebooks and Pipelines
Use a repeatable workflow to diagnose Spark, schema, parameter, dependency and pipeline failures.
Planned · View in editorial roadmap →Performance & Scale
Incremental Loads in Microsoft Fabric Without Reprocessing Everything
Patterns for loading only new and changed data into Fabric, with watermarks, change tracking and Delta MERGE, and how to handle late or corrected data.
Planned · View in editorial roadmap →
Performance & Scale7 tutorials
Performance & Scale
Working with Millions of Rows in Microsoft Fabric
Build a practical baseline for file layout, Spark execution and Delta writes at multi-million-row scale.
Planned · View in editorial roadmap →Performance & Scale
Working with Billions of Rows in Microsoft Fabric
Plan storage, partitioning, incremental processing and capacity for billion-row Fabric workloads.
Planned · View in editorial roadmap →Performance & Scale
Choosing a Good Partition Column for Delta Lake
Criteria for choosing a partition column: cardinality, query filters, write patterns and data volume per partition.
Planned · View in editorial roadmap →Performance & Scale
Choosing the Right Parquet File Size
How file size affects read parallelism, metadata overhead and write cost, and how to pick a target size for your engines.
Planned · View in editorial roadmap →Performance & Scale
MERGE into Delta Tables: Performance Patterns That Matter
How Delta MERGE works internally and the patterns that keep it fast: narrowing the target, partition and file pruning, and source deduplication.
Planned · View in editorial roadmap →Performance & Scale
Small Files in Delta Lake: Why They Hurt Performance
Where small files come from in Delta tables, how they slow down reads, writes and the transaction log, and how to measure the problem.
Planned · View in editorial roadmap →Performance & Scale
Fabric Performance Troubleshooting: A Practical Workflow
A step-by-step workflow for slow Fabric workloads: deciding whether the problem is capacity, Spark, SQL, storage layout or the query itself.
Planned · View in editorial roadmap →
Related published articles
Browse Fabric articles →
Cloud & Automation
Report Engine Architecture: Request to Result
Trace a report request through gateway, security, validation, cache, Fabric query, result construction and monitoring.
Cloud & Automation
What Is a Report Engine?
Define the report engine as a secure service between UI or API consumers and analytical data.
Microsoft Fabric
How to Make Microsoft Fabric Notebooks Faster
A practical workflow for reducing Fabric notebook startup, read, shuffle, transformation and Delta write time without guessing.
Certification
Prepare for Microsoft Fabric certification
Connect the official DP-600 or DP-700 skills outline to hands-on Fabric projects, troubleshooting, and production practice.