Microsoft Fabric: OneLake, Real-Time & Data Factory

Unified analytics platform with OneLake, Data Factory, and Real-Time Intelligence

Fabric Architecture

Architecture Diagram

┌─────────────────────────────────────────────────────────────────────┐
│                    MICROSOFT FABRIC ARCHITECTURE                     │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│  ┌─────────────────────────────────────────────────────────────┐   │
│  │                    MICROSOFT FABRIC                          │   │
│  │                                                               │   │
│  │  ONELAKE (Unified Storage)                                   │   │
│  │  ┌─────────────────────────────────────────────────────┐    │   │
│  │  │  OneLake Root                                        │    │   │
│  │  │  ├── Workspaces                                      │    │   │
│  │  │  │   ├── Sales Workspace                             │    │   │
│  │  │  │   │   ├── Lakehouse (Raw)                         │    │   │
│  │  │  │   │   ├── Lakehouse (Curated)                     │    │   │
│  │  │  │   │   ├── Warehouse                               │    │   │
│  │  │  │   │   └── Semantic Model                          │    │   │
│  │  │  │   └── Marketing Workspace                         │    │   │
│  │  │  └── Shortcuts (External Links)                      │    │   │
│  │  │       ├── ADLS Gen2                                  │    │   │
│  │  │       ├── S3 Buckets                                │    │   │
│  │  │       └── Dataverse                                  │    │   │
│  │  └─────────────────────────────────────────────────────┘    │   │
│  │                                                               │   │
│  │  ENGINES:                                                     │   │
│  │  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐      │   │
│  │  │ Data Factory │  │ Lakehouse    │  │ Warehouse    │      │   │
│  │  │ (Pipelines)  │  │ (Spark)      │  │ (SQL)        │      │   │
│  │  └──────────────┘  └──────────────┘  └──────────────┘      │   │
│  │                                                               │   │
│  │  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐      │   │
│  │  │ Real-Time    │  │ Power BI     │  │ Data         │      │   │
│  │  │ Intelligence │  │              │  │ Engineering  │      │   │
│  │  └──────────────┘  └──────────────┘  └──────────────┘      │   │
│  └─────────────────────────────────────────────────────────────┘   │
└─────────────────────────────────────────────────────────────────────┘

Fabric Lakehouse

# Fabric Lakehouse with PySpark
spark.read.format("delta").load("abfss://onelake@fabric-fabric.pbidedicated.microsoft.com/sales.lakehouse/Tables/raw_sales") \
    .filter("amount > 0") \
    .write.format("delta").mode("overwrite").save("abfss://onelake@fabric-fabric.pbidedicated.microsoft.com/sales.lakehouse/Tables/curated_sales")

# Fabric SQL Analytics Endpoint
# Connect via: fabric.sql.azuresynapse.net
# Use standard T-SQL queries

Fabric Data Factory

{
  "name": "fabric-pipeline",
  "type": "DataFactory",
  "properties": {
    "activities": [
      {
        "name": "CopyData",
        "type": "Copy",
        "inputs": [
          { "referenceName": "adls_source", "type": "DatasetReference" }
        ],
        "outputs": [
          { "referenceName": "lakehouse_sink", "type": "DatasetReference" }
        ]
      }
    ]
  }
}

ℹ️

Pro Tip: Use Fabric Shortcuts to link external storage (ADLS, S3) without copying data. This enables a unified data architecture without data movement.

Interview Questions

Q1: How does Fabric differ from Synapse Analytics? A: Fabric is a SaaS platform with unified storage (OneLake), compute engines, and Power BI. Synapse is a PaaS service with dedicated/serverless pools. Fabric provides simpler management and tighter integration.

Q2: What is the Lakehouse pattern in Fabric? A: Lakehouse combines data lake storage with data warehouse capabilities. In Fabric, Lakehouse uses Spark compute to query Delta tables stored in OneLake, providing SQL and programmatic access.

Q3: When would you use Fabric vs Azure Data Engineering services? A: Fabric for organizations wanting unified SaaS analytics with minimal infrastructure management. Azure services for teams needing more control, flexibility, or specific service capabilities.