Short and simple request: I would love to be able to 1-click edit my notebooks like I can with downstream pipelines (and Dataflows).             I know I can click the Notebook activity (1), click Settings (2) and click Open (3), but that way I need 3 clicks instead of 1! 🙂 ... View more

In the Fabric Data Factory, ten results are displayed after the pipeline execution, but it is not possible to verify which tables were processed by the executed activities. At this point, while it is possible to check the table from the input of the execution results, it would be helpful if it could be displayed directly in the execution results as it adds an extra step. Also, depending on the construction environment, it is assumed that processing may be carried out by specifying a file, and in that case, there is no need to display the table, so we consider it difficult to implement. However, if it can be realized, it would improve work efficiency, so I would appreciate it if you could consider it. ... View more

When creating connections to any database or api or any other source systems, we're not able to access the credentials from Keyvault secrets as similar to Azure Data Factory. Connection to an Azure Keyvault instance also helps in accessing the credentials in an easier and secure way. ... View more

its well known that intellisense has always been broken with things like ListList.Contains or pressing . after typing certain prefixes does not correctly show options, or typing null enter puts null.type in. Also a huge issue is no intellisense in Dataflows both need fixing ... View more

Orchestrating a refresh of a Dataflow Gen2 with CI/CD and Git support isn't possible in Fabric data pipelines. We request you to bring this feature in Fabric so that users can integrate these dataflow gen 2 with CI/CD and Git integration in data pipeline. ... View more

For low code users, it would be awesome if there was a Data Pipeline activity that can be used to run Vacuum of a table in a Lakehouse (or all tables in a Lakehouse).   For example, when using Copy Activity or Dataflow Gen2 to write to a Lakehouse table, the tables need to get vacuumed. But there is no automated, low-code way to do it. So users forget to vacuum the destination Lakehouse. ... View more

Please add support for mirroring to OneLake from on-premise SQL Server. ... View more

Please implement a mechanism to notify the admin and (or) workspace members when a pipeline fails ... View more

Please make it possible to open a dataflow gen2 without taking it over. I wish we could open a dataflow gen2 even if it is "owned" by someone else in the workspace. I think that the user who opens the dataflow gen2 should need to apply their own - or shared - data source connections in order to see any data in the query steps. Otherwise, they would be able to use the owner's connections to interact with the data sources, and I don't think that's a good idea. Because the owner might not want other workspace members to use his/her connections. So I think that the user who opens the dataflow gen2 should need to apply their own - or shared - data source connections in order to see any data in the query steps. I think it should be possible to open the item and start editing it, and not having to formally "take over" until you are ready to publish the changes. Or some times you just want to open it for inspection without making any changes. And if you do start to edit the dataflow, but then realize you aren't able to authenticate to all the data sources, then it should be possible to cancel so that the dataflow remains unchanged and the previous connections keep working. Would be nice to have: before a user saves (publishes) changes to the dataflow, there could be a validation step to check that the user has authenticated properly to all of the item's data sources and data destinations, so that they won't cause the dataflow to stop working. If the validation fails, the dataflow should keep running with the previous connections and the changes should be undone. ... View more

Enable to modify the mashup document of a Dataflow Gen2 by passing a variable from a pipeline before an execution of the Dataflow ... View more

We propose the ability for users other than the Dataflow Gen2 owner to collaborate on the same Dataflow Gen2. We think this feature would be useful and would like you to improve the functionality. ... View more

Right now, to view a pipeline schedule you have to go directly into the individual pipeline to view the schedule. It would be nice to be able to view and adjust pipeline schedules in one central location for all pipelines that an individual has access to, with view vs adjust capabilities limited to user permission levels. I believe this feature would help to easily coordinate and schedule multiple pipeline runs. Also, for users with only viewing permissions, it could be beneficial to see when new data is loaded. ... View more

Enable an experience that allows the end-user to setup incremental refresh for Dataflows Gen2 in Data Factory for Microsoft Fabric ... View more

Dataflows are supported by the Deployment pipelines, but there is no Git integration for dataflows. With the introduction of Git integration of workspaces, it would be fantastic if Dataflows could be stored and traced and reviewed in Git same like it is possible now for datasets and reports. ... View more

Current scheduling options for Data Pipelines in Microsoft Fabric are very limited, supporting only minute-based, hourly, daily, and weekly triggers, and lacking robust interval configurations or multiple triggers within a single pipeline run. This constrains scenarios such as running frequent updates during weekdays, then slowing down on weekends, or restricting half-hour refreshes to daytime hours. As a workaround, some users add extra pipelines or conditional logic to control time-based execution at the start of a pipeline, but this quickly becomes cumbersome to maintain. Proposed Feature • Allow users to define multiple schedules or a cron-like expression directly within a single pipeline’s scheduling settings. • Enable advanced recurring schedules that span specific day and time windows (e.g., “run every 30 minutes between 6 AM and 8 PM”), as well as once-per-month or custom intervals. • Provide a more intuitive user interface for scheduling multiple time windows without requiring additional pipeline objects or complicated conditional checks. Why This Matters • Reduces overhead of building and maintaining separate “child” pipelines or multiple triggers that only exist to address scheduling constraints. • Prevents complicated parameter and conditional logic in a single pipeline, which can be confusing to debug or update. • Empowers more granular and flexible scheduling (for example, different refresh frequencies on weekdays vs. weekends) without sacrificing readability. Current Workarounds (Short-Term) • Use conditional If activities at the pipeline’s start to check the current day or time, and proceed only if it falls within the desired schedule window. • Create separate pipelines and invoke them from a main pipeline, each using a different schedule trigger. • Call the pipeline via REST API or an external service (e.g., Power Automate, Logic Apps) that supports more advanced scheduling patterns ... View more

In ADF, you can parameterize a linked service so that one linked service could communicate with multiple database servers/databases. In Fabric, you would need a connection for every database. Please make connections parameterized so that working with an enterprise-level multi-tenant source database system would be easier. ... View more

When you create a connection to a warehouse, lakehouse or KQL DB, the connection is "absolute", meaning that the workspace ID is hardcoded into the connection. This gives issues when you deploy the pipeline to another workspace with deployment pipelines, because ADF will try to resolve the connection using the original workspace, instead of the new workspace. It can't find it, so the connection gives an error. You can work around the issue by parameterizing the connection entirely, as described in this blog post: https://sqlkover.com/dynamic-warehouse-lakehouse-connections-in-microsoft-fabric-data-pipelines/ However, it would be better if you could create a "relative" connection. This means: find the warehouse with the same name in the current workspace. ... View more

Several businesses have the need to exchange data via XLSX files. Due to company policies, the correct classification of sensitivity label for some files adds encryption to them. Power Query versions from Power BI Desktop or published Semantic Models(aka datasets) in Power BI Service/Fabric are already compatible with reading data from those encrypted files. Power Query online (attached to Dataflows Gen1 and Gen2) is not compatible to read encrypted files due sensitivity label policies Since best practices suggest that you should move your transformations as upstream as possible (which for the business user means using Dataflows), this is a much-needed feature. ... View more

Hi, We are experiencing significant issues with deploying Dataflow Gen 2 from development to production. Currently, we are using the manual export and import method, saving them to a local drive. Handling over 100 tables makes this manual method very time-consuming. Could we have support for a deployment pipeline with Dataflow Gen 2? If it is already planned, could we know the release date? Thank you. ... View more