fabric-lakehouse
Microsoft Fabric Lakehouse storage for unified tabular and non-tabular data with Delta Lake, SQL analytics, and fine-grained security.
- Combines data lake flexibility with data warehouse management through Delta Lake format, ACID transactions, versioning, and SQL endpoints for T-SQL querying
- Organizes data via schemas (folders under Tables), shortcuts (virtual links to internal/external sources), and materialized views for optimized query performance
- Supports multiple data formats: Delta tables, CSV, Parquet, and any file type; includes column-level and row-level security through OneLake RBAC
- Shortcuts enable cross-workspace, cross-cloud, and external data access without copying (ADLS Gen2, S3, Google Cloud Storage, Dataverse)
- Built-in optimization tools: V-Order for semantic model performance, OPTIMIZE command for file compaction and Z-ordering, and Vacuum for storage cleanup
When to Use This Skill
Use this skill when you need to:
- Generate a document or explanation that includes definition and context about Fabric Lakehouse and its capabilities.
- Design, build, and optimize Lakehouse solutions using best practices.
- Understand the core concepts and components of a Lakehouse in Microsoft Fabric.
- Learn how to manage tabular and non-tabular data within a Lakehouse.
Fabric Lakehouse
Core Concepts
What is a Lakehouse?
Lakehouse in Microsoft Fabric is an item that gives users a place to store their tabular data (like tables) and non-tabular data (like files). It combines the flexibility of a data lake with the management capabilities of a data warehouse. It provides:
- Unified storage in OneLake for structured and unstructured data
- Delta Lake format for ACID transactions, versioning, and time travel
- SQL analytics endpoint for T-SQL queries
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