Paths

Learn Microsoft Fabric

Ordered, guided paths — each step builds on the last, and every claim is grounded in cited sources. Looking for architecture patterns instead? Browse the architecture gallery →

Fabric Foundations

A guided first pass across the whole platform -- what each workload is for and how they fit together, before going deep on any one of them.

For: New to Microsoft Fabric, or evaluating the platform for the first time.

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  1. Platform & Governance in Microsoft FabricArticle
  2. Storage & OneLake in Microsoft FabricArticle
  3. Data Engineering & Integration in Microsoft FabricArticle
  4. Warehousing & SQL in Microsoft FabricArticle
  5. BI & Semantic Models in Microsoft FabricArticle
  6. Real-Time Intelligence in Microsoft FabricArticle
  7. AI & APIs in Microsoft FabricArticle

Spark on Fabric

From your first Spark session to Native Execution Engine internals and the Delta write path.

For: Data engineers writing or tuning Spark notebooks on Fabric.

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  1. The Spark engine in Microsoft Fabric — BeginnerLesson
    ~12 min · You can start a Spark notebook in Fabric, reason about which pool it's running on, and write Delta tables with basic optimization settings applied.
  2. Architecting Spark Workloads in Microsoft FabricLesson
    ~13 min · You can architect a Spark workload in Fabric with session-startup latency, write-path cost, and orchestration placement as explicit, justified design decisions.
  3. Spark Engine Internals in Microsoft Fabric: Native Execution, Compute Topology, and the Write PathLesson
    ~18 min · You can explain, mechanism by mechanism, why a given Spark job in Fabric is fast or slow — from NEE acceleration down to the Delta write path — without guessing.
  4. Apache Spark in Microsoft Fabric: A Practitioner's Guide to Compute, Delta Writes, and the Native Execution EngineArticle

Lakehouse & Delta Tables

How Delta tables work in a Fabric Lakehouse, from your first table to storage internals and maintenance mechanics.

For: Data engineers designing or maintaining Lakehouse tables.

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  1. Delta tables in Fabric — BeginnerLesson
    ~12 min · You can explain why one Delta table is readable from Spark, SQL, and Power BI without a separate copy, and avoid the most common early mistakes.
  2. Delta Tables in Microsoft Fabric: Architecting for Multi-Engine AccessLesson
    ~14 min · You can architect a lakehouse table so it stays readable and performant across Spark, SQL, and Power BI, and explain the role Delta's transaction log plays in that guarantee.
  3. Delta Tables in Microsoft Fabric: Storage Internals, V-Order, and Maintenance MechanicsLesson
    ~18 min · You can reason about Delta table performance from the transaction log outward — why a query skips files, why V-Order helps a given consumer, and what a deletion vector actually changes at read time.
  4. Microsoft Fabric Lakehouse: Architecture, SQL Analytics, and Delta OptimizationArticle

dbt on Fabric Warehouse

Running dbt against Fabric, from your first model to adapter mechanics and incremental-run cost.

For: Analytics engineers adopting dbt on Fabric Warehouse or Lakehouse.

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  1. dbt with Microsoft Fabric — Beginner: models, the adapter, and your first runLesson
    ~12 min · You can explain what dbt adds on top of Fabric's built-in transformation tools, and set up and run a dbt project against a Fabric Warehouse.
  2. dbt with Microsoft Fabric — Intermediate: auth, CI/CD, orchestration, and tool placementLesson
    ~15 min · You can set up a CI/CD-ready dbt project against Fabric Warehouse, orchestrate it, and justify choosing dbt over Fabric's built-in transformation tools for a given workload.
  3. dbt with Microsoft Fabric — Expert: adapter mechanics, incremental costs, and failure modesLesson
    ~15 min · You can reason about the cost and failure modes of a dbt-fabric incremental run from first principles, and know which adapter behaviors are undocumented rather than guess at them.
  4. Fabric Data Warehouse: Architecture, Caching, GPU Acceleration, and Best PracticesArticle

Fabric IQ & the Ontology Layer

What the ontology item is, how to architect one, and its open internals.

For: Architects and engineers building a shared semantic layer for AI agents.

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  1. Fabric IQ and the Ontology Item — BeginnerLesson
    ~12 min · You can explain what Fabric IQ adds on top of a plain schema-and-prompt approach to AI agents, and name its two anchor items.
  2. Fabric IQ Ontology Architecture — IntermediateLesson
    ~13 min · You can architect an ontology layer for a real domain and explain why grounding an agent in it produces more reliable answers than schema-and-prompt alone.
  3. Fabric IQ Mechanics and Open Internals — ExpertLesson
    ~12 min · You know exactly which Fabric IQ claims are Microsoft-documented, which are field-reported only, and which remain genuinely undocumented — and you won't conflate the three.
  4. Fabric IQ: Giving AI Agents a Shared Business VocabularyArticle