OneLake Shortcuts: Data Without Duplication

What are OneLake shortcuts?

Simple explanation

Think of a shortcut on your desktop.

The shortcut icon points to a file somewhere else on your computer. Double-click the shortcut and it opens the real file. The file itself doesn’t move — you just have a convenient pointer to it.

OneLake shortcuts work the same way for data. You create a pointer in your lakehouse that points to data stored elsewhere — another lakehouse, Azure Data Lake Storage, Amazon S3, or Google Cloud Storage. Your PySpark notebooks and SQL queries read the data as if it’s local, but no data is copied.

This means zero duplication, zero extra storage cost, and always-fresh data.

Shortcut types

Shortcuts work across clouds and across Fabric workspaces
Source	Authentication	Typical Use Case
Another Fabric lakehouse	Delegated (user identity or workspace identity)	Cross-workspace data sharing without duplication
Azure Data Lake Storage Gen2	Service principal or org identity	Existing data lake → Fabric without migration
Amazon S3	Access key + secret key	Multi-cloud — read AWS data from Fabric
Google Cloud Storage	Service account key	Multi-cloud — read GCS data from Fabric
Dataverse	Org identity	Power Platform data accessible in Fabric analytics
S3-compatible (MinIO, etc.)	Access key + secret key	On-premises or custom S3-API storage

Where shortcuts can point

Tables/ section → shortcut appears as a Delta table (queryable via Spark and SQL endpoint)
Files/ section → shortcut appears as a folder of files (any format)

Creating a shortcut

Open a lakehouse in Fabric
Right-click on Tables/ or Files/ → New shortcut
Choose the source type (Fabric, ADLS, S3, etc.)
Provide connection details and credentials
Select the target folder or table
The shortcut appears instantly — no data copy, no waiting

Scenario: Anika's multi-cloud shortcuts

ShopStream’s data lives in three places:

Product catalog — existing Azure Data Lake Gen2 (legacy system)
Payment data — Amazon S3 (payment provider stores data there)
Marketing events — another Fabric lakehouse in the marketing workspace

Instead of copying data into her lakehouse, Anika creates three shortcuts:

/Tables/ProductCatalog → ADLS Gen2 shortcut
/Files/PaymentRaw/ → S3 shortcut
/Tables/MarketingEvents → Fabric lakehouse shortcut

Her PySpark notebooks join across all three as if they’re local tables. Zero data duplication. Always fresh.

Shortcuts vs mirroring

This comparison appears frequently on the exam.

Shortcuts point to data; mirroring copies data — choose based on source type and resilience needs
Feature	Shortcuts	Mirroring
Data copied?	No — reads from source at query time	Yes — continuous replication into OneLake as Delta tables
Latency	Real-time (reads source directly)	Near real-time (minutes — CDC-based replication)
Storage cost	None (no duplication)	OneLake storage for the replicated copy
Source types	ADLS, S3, GCS, Dataverse, Fabric items	Azure SQL, Cosmos DB, Snowflake, PostgreSQL, MySQL, Spark catalog
Write to source?	No (read-only)	No (read-only replica)
Offline access?	No — if source is down, shortcut fails	Yes — replicated data in OneLake survives source outages
Best for	Accessing file-based or lake-based data without duplication	Replicating operational databases for analytics without ETL code

Exam tip: Shortcut vs mirror decision

Use a shortcut when:

The source is a file store (ADLS, S3, GCS) or another Fabric item
You want zero data duplication
The source is always available (no offline access needed)

Use mirroring when:

The source is a relational database (SQL, Cosmos DB, Snowflake)
You need a local replica that survives source outages
You want automatic CDC-based replication without building ETL pipelines

Key exam pattern: “Access data without copying” → Shortcut. “Replicate a database” → Mirroring.

Shortcut considerations

Consideration	Detail
Performance	Reading from external shortcuts (S3, GCS) may be slower than local OneLake data due to network latency
Security	Shortcuts inherit lakehouse permissions — but the user must also have access to the source
Cost	No OneLake storage cost, but egress charges may apply from AWS or GCP
Schema	Shortcut to a Delta table inherits its schema; shortcut to files doesn’t enforce schema
Write	Shortcuts are read-only — you cannot write data through a shortcut

Question

What is an OneLake shortcut?

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Answer

A virtualised reference that lets a lakehouse access data stored elsewhere (ADLS, S3, GCS, another Fabric lakehouse) without copying the data. Queries read the source directly. Zero duplication, zero extra storage.

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Question

Can you write data through a OneLake shortcut?

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Answer

No. Shortcuts are read-only. You can query the data via Spark or SQL endpoint, but writes must go directly to the source storage.

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Question

What happens if the external source behind a shortcut goes offline?

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Answer

Queries against the shortcut fail — there's no local copy to fall back on. If you need offline access, use mirroring instead (which creates a replicated copy in OneLake).

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Knowledge Check

Anika needs to query data stored in Amazon S3 from a Fabric lakehouse. She does not want to copy the data or incur OneLake storage costs. Which feature should she use?

Knowledge Check

The source behind a lakehouse shortcut (pointing to ADLS Gen2) experiences a 2-hour outage. What impact does this have on Fabric queries that use the shortcut?

Next up: Mirroring: Real-Time Database Replication — bring operational databases into Fabric without building a single pipeline.