Fabric Ideas

Add functionality to Manage (Data Model Settings) Page Currently this just shows a grayed out >Data Source Credentials which cannot be maintained in the Power BI Service. Add functionality to manage gateway like PBIX Reports Add functionality to manage paramaters (see below for more detail) Ability to manage parameters in the Power BI Service for Power BI Report Builder Paginated Reports Currently paginated reports (.rdl) do not have the parameter flexibility like the standard power bi reports (.pbix) where parameters can be changed on the back end (e.g. pointing test to test and dev to dev database via a parameter used for the data source).   It would be awesome for both Internal paginated report parameters AND power query parameters to be managable from the power bi service in the manage screen.   Rename the Manage and Settings menu options in the Power BI Service (elipses options on RDL files) For RDL, Manage option appears to take user to a screen similar to PBIX Data Model 'settings' while Settings appears to take you to Report 'settings'. To make things easier to follow, simply rename Manage to Report Settings and Settings to Data Model Settings.   Workspace level setting Add functionality to set which roles can create, read, update, and/or delete ALL associated subscriptions rather than just the ones created by current user for. ... View more

I would like to request an update to the public information attached below in the Japanese version. The English version is up to date, but the Japanese version has not been updated since 2024/11/20.   JP URL: https://learn.microsoft.com/ja-jp/fabric/database/mirrored-database/azure-databricks-tutorial EN URL: https://learn.microsoft.com/en-gb/fabric/database/mirrored-database/azure-databricks-tutorial   Reason for updating: I confirmed in the English version that a new "Prerequisites" was added. The Japanese version does not have this notation, so customers cannot test it following the correct procedure. ... View more

When I open a Notebook, it automatically opens the expanded Explorer pane (to the left). I rarely use this, so every time I open a Notebook I have to: - Collapse the Explorer pane (to the left) - Click on the View tab in the ribbon (at the tip) - Open the Table of contents pane (to the right) - Wait for the Table of contents to load   I would like to be able to persist the view/layout for each notebook (or alternatively as a user setting) so the next time I open the notebook I will by default see the Table of contents instead of the expanded Explorer pane.   (Additionally, I would love to be able to move the panes between the left and right sides, but that's less important.)   This would be a quality of life improvement that would save developers time and make the development experience much smoother. ... View more

we use whl files and create libraries to make configurations and common code accessible across all notebooks in our Data Engineering solution. But publishing these files to environment is not a great experience. I need to try multiple times publishing with no luck. It is hard to predict if publishing was successful or not. It would be helpful if can see the libraries, whl files etc available at cluster level. ... View more

Please fix the SQL Analytics Endpoint sync delays. Many users have been surprised and are receiving old data because of the Lakehouse SQL Analytics Endpoint sync delays. We want Fabric to handle this automatically, so we don't need to think about it. ... View more

Lakehouse data access roles are currently limited to 250. This limitation constraints data engineering team from following least access privileges principles. We tried to make use Lakehouse data access roles to restrict data access to user by entity. But, this number limitation is constraining us. ... View more

Hi Folks, There are currently two flavors of notebooks (lakehouse + warehouse). I have a client that wanted to leverage TSQL notebooks. However, there is no post deployment option for setting the default warehouse. Is this required feature on a roadmap somewhere? Sincerely John Miner PS:   Pleasantly surprised on the state of this feature. It is getting better every day! EX: Image below shows missing option in my simple test environment. ... View more

Lakehouses, and more importantly the data inside them, are not recoverable if the the lakehouse is deleted. There is also no way to recover a prior lakehouse if the data needs to be rolled back to a previous state. BCDR was recently released but is only for capacity disaster recovery and is too cumbersome as it has an extra cost along with deploying in another region. We need a way to recover a lakehouse and its history, if it has been deleted or if the data has been corrupted. ... View more

Data Warehouses and Data Lake House are tied to the user account of their creator. Which means, when the creator leaves an organization and the account is disabled/deleted, the lakehouse and data warehouse stop functioning. This is not sustainable for enterprise organizations that may attempt to build solutions off lakehouses and data warehouses. Either associate the lakehouse and warehouse ownership with the workspace (which means the workspace will need an identity for permission setting at the data lake) or allow administrators to reassign ownership of the lakehouse and data warehouse. Currently there is a powershell script for data warehouse, there isn't for lakehouse. Which means that the lakehouse rebuilt and downsteam artifacts need to be modified. ... View more

There is an ofter large delay for data to become available via the T-SQL Endpoint. With barely 142 delta tables, some newly created delta tables wont even be available until we manually hit refresh next to the warehouse endpoint in the T-SQL view. While the data is readily available to spark, it takes a while to become available to users on Management Studio. ... View more

Certain fabric artifacts, such as notebooks, cannot have deployment rules specified after being deployed from one workspace to another, as we are not the owners of those artifacts. We would like the Product Team to introduce a feature that allows us to take ownership of these artifacts or enable users with at least contributor access to the workspace to set the deployment rules. ... View more

Hi! Request: please add a standard activity for refreshing the SQL Analytics endpoint as a feature directly in Data Pipelines OR make an option (check box) in the Semantic Model refresh activity (which is in preview) to refresh connected SQL Analytics endpoint. Problem: I have a standard activity for refreshing my Semantic Model, but the SQL Analytics endpoint which is one step before is not automatically refreshed. ... View more

Power Query, with its intuitive user interface, has revolutionized self-service data transformation in Microsoft’s ecosystem, allowing users to perform complex transformations without needing deep coding skills. However, while Power Query’s UI is user-friendly, it generates M code, which when processed has its limitations in handling large-scale data processing or more advanced transformations. On the other hand, Apache Spark is a powerful, scalable data processing engine, designed to handle big data workloads efficiently. However, its native interface, especially when working in a Spark notebook, is less accessible to users without coding expertise. There’s an opportunity here: to combine the simplicity and accessibility of Power Query’s UI with the efficiency and scalability of Spark. This will allow users to leverage Spark’s processing power without sacrificing the ease of transformation that Power Query provides. Description of the Idea A Unified Power Query UI for Spark Transformations in Microsoft Fabric The core idea is to extend the Power Query/Dataflow UI within Microsoft Fabric so that, instead of generating M code, it writes transformations directly into a Spark notebook. This would provide users with the best of both worlds: User Experience: The familiar, easy-to-use drag-and-drop UI of Power Query that democratizes data transformation, allowing analysts and business users to manage data transformations without needing to write complex code. Performance and Scalability: By generating Spark code under the hood, the solution leverages Spark’s distributed processing capabilities. This ensures that even complex transformations on large datasets can be handled efficiently, taking full advantage of Spark’s low CU usage, speed and scalability. Key Features of This Approach: Seamless Integration: The UI would allow users to visually build their transformation logic in the same way they do in Power Query, while behind the scenes, Spark code is written and executed within a Spark notebook. Advanced Performance: Leveraging Spark’s powerful distributed architecture, this approach would handle large datasets more efficiently than Power Query’s current M engine. Transformations could be executed at scale, supporting larger and more complex use cases. Interoperability: This solution would be integrated within Microsoft Fabric, making it easy to move between low-code/no-code interfaces and deeper programmatic control when needed. Users could still open the Spark notebook generated from their UI transformations to tweak or optimize the code further if desired. Efficiency Gains for Enterprises: By using the Power Query UI in the frontend and Spark as the backend, users can significantly reduce time spent on large data transformations. ... View more

if we get an option to connect to Azure KeyVault in Microsoft Fabric in Synapse data engineering through linked Service , We can retrieve values from keyvault which are sensitive in Nature. ... View more

I created a Notebook under a Lakehouse. I then added/attached a second lakehouse to the notebook. Under the Explorer, it shows "Lakehouses / 2 item(s) added" with the expand ">" icon. I click that icon and see ONLY ONE lakehouse listed (the default). ... View more

T-SQL temp tables support over multiple notebooks cells so that we can benefit from the usage of markdown cell features to document our code through out with a complete T-SQL script. ... View more

Creating an environment gives you a nice UI to set a list of Python packages to install by default The user thinks : “Oh cool, this will be faster than doing %pip install every time I start a notebook” The reality is that it now takes 3 minutes to start Spark, instead of 10 seconds to run "%pip install" Either fix the UI to warn users, or fix the startup time. ... View more

Write data directly into a data warehouse using the Fabric notebook, which utilizes Spark (let Fabric handle the staging process behind the scenes). This functionality resembles what is currently available in Synapse Analytics Workspace. ... View more

We need true role playing capabilities for dimensions in Fabric. Currently, you can include a table only a single time in a semantic model that uses DirectLake. This makes it impossible to use a dimension as a role playing dimension - for example, our date table as admit date, discharge date, surgery date, etc. Also the same for providers - there can be an admitting provider, discharge provider, attending provider, surgeon, primary care physician, etc. We need the ability to: Use a table multiple time in a semantic model built in the service Be able to rename the table, for example rename a generic "date" table to admit date, discharge date, etc. Still have everything work properly with DirectLake The only workaround currently is to create multiple copies of the table. This not only wastes space, but also means separate ETLs have to be updated if there's any change to the base table. Thanks, Scott ... View more