Uses of Surrogate keys :
- Ensures consistency and integrity across the data warehouse.
- Surrogate keys also simplify the relationships between tables, as they can be used as primary keys and foreign keys without any additional logic or transformation.
- Surrogate keys can improve the performance of queries and joins, as they are usually shorter and simpler than natural keys.
Creating a Dimension Table using the new IDENTITY Feature in Fabric Datawarehouse
CREATE TABLE dbo.Dim_Product
(
ProductId BIGINT IDENTITY,
ProductName VARCHAR(100),
Category VARCHAR(100),
ListPrice VARCHAR(100)
);Limitations :
- Currently Fabric Datawarehouse does not support the IDENTITY with Seed or increment like IDENTITY(1,1) which we normally do in SQL.
- The IDENTITY column data need not be consequetive or have a definite range.
- The IDENTITY column should always be of a BIGINT datatype.
- IDENTITY column cannot be updated.
COPY INTO dbo.Dim_Product (ProductName,Category,ListPrice)
FROM 'https://<onelake>/<workspace-id>/Files/products.csv'
WITH (
FILE_TYPE = 'CSV'
);
We can see the unique bigint value getting generated for the ProductID which are unique across each row.Identity columns eliminate MAX + ROW_NUMBER patterns, key‑control tables, and race conditions—bringing warehouse‑managed surrogate keys back where they belong.
Conclusion - A small feature with a big architectural impact
Surrogate keys are not an optional design choice in a dimensional warehouse—they are foundational. With the introduction of Identity columns in Microsoft Fabric Warehouse, surrogate key generation finally becomes what it should be: a native responsibility of the warehouse itself.This shift has a ripple effect across the entire analytics stack. Pipelines get simpler because they no longer need to “think” about keys. Ingestion becomes safer under parallel and streaming workloads. Dimensional models become easier to reason about, easier to migrate from traditional SQL warehouses, and far more resilient at scale. Perhaps most importantly, data engineers and warehouse designers can focus on modeling and business logic instead of defensive key‑management patterns.
Identity columns may look like a small addition on paper, but in practice they remove one of the most persistent sources of complexity in modern data warehouse implementations. For anyone building star or snowflake schemas in Fabric—especially at enterprise scale—this is a genuinely game‑changing capability.As Fabric Warehouse continues to mature, features like Identity columns signal a clear direction: enterprise‑grade warehousing, simplified, without sacrificing correctness, performance, or modeling best practices.
Microsoft Employee
