Microsoft Fabric Updates Blog

Updates to default data destination behavior in Dataflow Gen2

When you have a Lakehouse or Warehouse and you want to load data into it, you can use Dataflow Gen2 as an easy, low-code way for landing your data with the right shape.

You can always create a stand-alone Dataflow Gen2 and use the data destinations to load your data in any Fabric Lakehouse or Warehouse, but to speed up your development, there are some easy other ways to land your data faster.

This blog is to update you on the experience and important changes that were made.

Within the Lakehouse or Warehouse experience, you can get data through a variation of options.

Select new dataflow gen 2 from get data dropdown in Lakehouse or Warehouse

When choosing Dataflow Gen2 from either the Lakehouse or the Warehouse, the data destination experience is slightly different from a ‘standard’ Dataflow Gen2 that was created from the workspace.

By default, any query that you create will have the Lakehouse or Warehouse you started from set as the data destination. If you hover over the data destination icon, you can see that the destination is labeled as ‘default destination’. This is different from the standard Dataflow Gen2, where you explicitly have to assign a query with a data destination.

Hover over the data destination icon to see that the destination is labeled as defautl destination

With the default destination, the settings are set to a default behavior that cannot be changed. This are the behaviors for both Lakehouse and Warehouse default destination:

BehaviorLakehouseWarehouse
Update methodReplaceAppend
Schema change on publishDynamicFixed

Note: Previously, update method for Lakehouse was append. This is now changed to replace.

To edit the settings of an individual data destination, use the gear icon to edit the destination. When you edit the individual data destination, this change is only affecting the specific query. It is currently not possible to change the behavior of the default destination.

Related blog posts

Updates to default data destination behavior in Dataflow Gen2

June 24, 2024 by Justin Barry

When we talk about Microsoft Fabric workspace collaboration, a common scenario is developers and their teams using a shared workspace environment, which means they have access to “live items”. A change made directly within a workspace would override and affect all other developers or users utilizing that workspace. This is where git becomes increasingly important … Continue reading “Microsoft Fabric Lifecycle Management: Getting started with development in isolation using a Private Workspace”

June 21, 2024 by Marc Bushong

Developing ETLs/ELTs can be a complex process when you add in business logic, large amounts of data, and the high volume of table data that needs to be moved from source to target. This is especially true in analytical workloads involving relational data when there is a need to either fully reload a table or incrementally update a table. Traditionally this is easily completed in a flavor of SQL (or name your favorite relational database). But a question is, how can we execute a mature, dynamic, and scalable ETL/ELT utilizing T-SQL with Microsoft Fabric? The answer is with Fabric Pipelines and Data Warehouse.