Lakehouse-Architektur

Last modified by Dimitri Rupp on 2026/06/11 09:30

πŸ’§ Fabric Lakehouse

Information

A Lakehouse in Microsoft Fabric is a unified data architecture that merges the scalability of a data lake with the structure and performance of a data warehouse, offering a single platform for storing, managing, and analyzing structured and unstructured data.

πŸ—„οΈ Storage

Data is stored in Delta tables, which support ACID transactions, schema evolution, and time travel. A Lakehouse contains two zones β€” Tables and Files.

  • Tables β€” managed Delta tables with full metadata support
  • Files β€” unmanaged storage for raw data (CSV, Parquet, images, etc.), accessible via Spark but not queryable via SQL endpoint unless converted to Delta

πŸ”„ Transformation

Dataflows Gen2, Notebooks (PySpark / Spark SQL), and Pipelines enable ingestion, cleansing, and transformation. These tools integrate natively with Lakehouses for modular, reproducible workflows.

πŸ” Access

Lakehouses expose a SQL endpoint for T-SQL queries. Access is governed via Microsoft Entra ID, with support for workspace roles, item-level permissions, and Service Principals for secure external automation.

πŸ—οΈ Layers in our architecture

The SPL Fabric architecture follows the medallion pattern with three layers:

flowchart LR
    SRC[📂 Source Systems] --> B[🥉 Bronze
Landing zone] B --> S[🥈 Silver
Transformation] S --> G[🥇 Gold
Business-ready] G --> CONS[📊 Consumers
Power BI / Excel / Board] style B fill:#cd7f32,color:#fff style S fill:#c0c0c0,color:#000 style G fill:#ffd700,color:#000

For detailed access instructions, see Get data from Lakehouse.

πŸ“‹ Source-specific Bronze Lakehouses

The Bronze layer is split into individual Lakehouses per source system:


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Status: Migriert β€” Team-Review ausstehend Β· Owner: (festlegen) Β· Letzter Review: 2026-06-11