File level commit - Need the ability to edit the commit description
I tried the recently announce file level commit for Fabric items. One notable issue I have with the feature (testing this with a Fabric warehouse, I'm assuming this would hold true for other items): While I am able to pick files to commit to source control, I am unable to edit the commit description. The current commit has a generic message "Committing 1 item from workspace <workspace_guid>". To best make use of this feature, it would be helpful to be able to edit the commit description so I can clarify what is in the commit.
Schedule pipeline as Service Principal
It would be beneficial to be able to specify an anonymous sp or user account while creating a schedule to run a pipeline directly in the Fabric GUI. This is currently only possible via the rest api and an external scheduler. Ti would be nioce to have run as sp , enterprise app or user option.Fabric Workspace Operator Role for Pipeline Monitoring and Rerun Operations
Many organizations have dedicated production support and operations teams responsible for monitoring Microsoft Fabric pipelines and responding to failures. Currently, the available workspace roles are Admin, Member, Contributor, and Viewer. While Viewers can monitor content, they cannot rerun failed pipelines. Contributors can rerun pipelines, but they also have permissions to modify pipeline definitions and other workspace artifacts. This creates a governance gap for enterprises that require segregation of duties between development and operations teams. Proposed Solution Introduce a new built-in Operator workspace role with permissions such as: Allowed View pipeline definitions Monitor pipeline runs and run history View execution logs and error details Manually trigger pipeline execution Rerun failed pipeline runs Cancel running pipeline executions Access workspace monitoring capabilities Not Allowed Create, edit, or delete pipelines Create, edit, or delete Fabric artifacts Modify notebooks, lakehouses, warehouses, or dataflows Manage workspace access or permissions Change workspace settings Connect/disconnect Git repositories Business Value This role would: Support enterprise segregation of duties requirements. Enable production support teams to resolve operational issues without granting development permissions. Reduce the risk of accidental changes in production workspaces. Improve governance and compliance. Align Microsoft Fabric with operational models commonly used in enterprise data platforms. Many organizations need a role that sits between Viewer and Contributor, providing operational control without development privileges. An Operator role would significantly improve security, governance, and supportability for Fabric Data Factory workloads. Use Case: Production support team monitors Fabric pipelines, investigates failures, and reruns failed executions, but should not be able to modify pipeline definitions or other workspace assets.
Enable Gateway Cluster Reassignment for Data Sources
As a large enterprise managing thousands of Power BI gateway connections across multiple clusters, we frequently encounter a significant operational challenge due to the current 1,000 connection limit per cluster. This limitation necessitates the manual recreation of data sources and rebinding of datasets when exceeding capacity, leading to a time-consuming and error-prone administrative process. We request a feature that enables Power BI administrators to seamlessly reassign existing data sources between gateway clusters. This functionality should be accessible via a user-friendly dropdown or bulk operation within the Power BI Service or Admin Center, eliminating the need to recreate connections from scratch on a new cluster.Rule to force only HC Sessions while working with interactive notebooks
As a Fabric Platform Admin, I would like to force users of specific workspaces to only be allowed to spin-up and use High Concurrency (HQ) Sessions while working interactively with notebooks. This can help with best capacity utilization and faster notebook startups.
Enable Direct Addition of Fabric Data Agents to Microsoft 365 Copilot
Please enable users to add and invoke a Fabric Data Agent directly as a specialized agent in a Microsoft 365 Copilot multi-agent solution. In our current setup, we can’t add a Fabric Data Agent directly to M365 Copilot, so we connect to it through Fabric IQ Data MCP. This approach raises a concern that we need to separately verify whether requests are routed to and handled by the intended Fabric Data Agent. That additional validation makes configuring and testing the multi-agent solution more complex. We request the ability to select and add a Fabric Data Agent directly as a subagent in the M365 Copilot multi-agent configuration, allowing the parent agent to delegate tasks to it directly. This would reduce the additional validation required for the intermediate MCP connection and make the multi-agent setup simpler and more transparent. This request is not a report of a defect in Fabric IQ Data MCP; it is a request for direct Fabric Data Agent integration in M365 Copilot. We also request that the Fabric Data Agent’s existing authentication, data-access permissions, and security policies continue to be enforced when using this direct integration. References: Consume a data agent in Microsoft Copilot Studio (preview) Consume a Fabric data agent as a tool in Microsoft Copilot Studio
Schedule Data Pipeline to run as a Service Principal
Please make a UI (user interface) option to schedule a Data Pipeline to run in the user context (security context) of a Service Principal instead of my personal user. This should also have the effect that any Notebooks within the Data Pipeline are run in the security context of that Service Principal.Databricks Autoloader equivalent for Fabric Lakehouse
We need something low code close to autoloader of databricks in Fabric, which is built on top of structured streaming, that can load data incrementally from lake files in ADLS/One Lake into lakehouse as delta table, that can do automatic schema evolution checks as well. Thanks, Gaurav📉 How Would You Investigate a 20% Drop in Revenue?
A data analyst shouldn’t stop at identifying what happened. The real questions are: Where did the decline occur? → Why did it happen? → What caused it? → What should we do next? By analyzing regions, products, customers, time periods, and key business metrics, raw data can reveal the root cause behind the numbers. Good data analysis turns numbers into decisions. 📊 #DataAnalysis #BusinessIntelligence #PowerBI #MicrosoftFabric #DataAnalytics
