Enhance Power BI with Advanced AI-Powered DAX Optimization and Performance Monitoring
Description I would like to suggest introducing advanced AI-powered DAX optimization and performance monitoring capabilities directly into Power BI. As Power BI solutions become more complex, developers often spend significant time identifying inefficient DAX measures, optimizing queries, troubleshooting slow visuals, and improving report performance. An AI-powered optimization assistant could help developers automatically identify performance bottlenecks, recommend optimized DAX expressions, detect unnecessary calculations, and suggest improvements to data models. Key Proposed Features AI-Powered DAX Optimization: Automatically analyze DAX measures and recommend optimized expressions. Performance Monitoring: Identify slow-running queries, visuals, and inefficient calculations. Smart Recommendations: Provide actionable suggestions to improve report performance. DAX Explanation: Explain complex DAX expressions in simple language. Automated Error Detection: Identify potential DAX errors and recommend corrections. Query Optimization: Recommend improvements for Power Query and data model performance. Performance Insights Dashboard: Provide a centralized view of report performance and optimization opportunities. Business Value These capabilities could significantly reduce development time, improve report responsiveness, simplify troubleshooting, and help Power BI developers build more scalable and efficient analytics solutions. Expected Impact This enhancement would benefit Power BI developers, data analysts, BI engineers, and organizations working with large and complex datasets. Bringing AI-powered DAX optimization and performance monitoring directly into Power BI would make analytics development smarter, faster, and more accessible.
notebookutils.credentials.getToken: Add more audience keys
Currently, only 4 audiences are listed in the docs: Audience key Resource Use case storage Azure Storage Access ADLS Gen2 and Blob Storage pbi Power BI Call Power BI and Fabric REST APIs keyvault Azure Key Vault Retrieve Key Vault secrets kusto Synapse RTA KQL DB Connect to Azure Data Explorer https://learn.microsoft.com/en-us/fabric/data-engineering/notebookutils/notebookutils-credentials?tabs=python#get-token Please add Azure SQL Database to this list. That would be very useful for Workspace Identity. Thanks!Enhance Microsoft Fabric Learning with Real-World Projects and Hands-On Practice
I would like to suggest introducing more hands-on learning resources, real-world projects, and practical exercises across Microsoft Fabric. It would be beneficial to have: More end-to-end Microsoft Fabric projects. Advanced SQL, PySpark, and Data Engineering challenges. Real-world Power BI and Direct Lake scenarios. More DP-600, DP-700, and DP-800 exam preparation resources. Interactive exercises with step-by-step solutions. Dedicated learning paths for beginners and experienced professionals. These improvements would help community members strengthen their practical skills, prepare for Microsoft certifications, and become industry-ready. Thank you to the Microsoft Fabric team for continuously improving the community and learning experience.File Level Deployment (especially Warehouse and Fabric SQL) for Fabric Deployment Pipelines
Fabric deployment pipelines currently support deploying items in their entirety. The announcements from Barcelona introduced file-level commit for Git, supporting more granular controls for source control of larger items like warehouses and databases. For organizations that want simpler approaches to CI/CD, it would be helpful to have file-level deployment as an option. For SQL-based items like warehouses and databases, it would be similar to the Schema Compare capabilities in Visual Studio, where you can pick specific objects in the item, identify dependencies, and have a publish script to review detailing how the deployment will be done.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.📉 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
Auto-generate INSERT VALUES scripts for configuration data migration across environments
Hi Fabric Team, I would like to suggest a feature that could significantly simplify deployment and environment promotion activities. Today, when configuration tables contain reference or application settings data (for example mappings, parameters, business rules, or integration configurations), moving these records from a Development environment to Test or Production often requires manually creating INSERT INTO ... VALUES scripts. It would be extremely useful to have a built-in capability in Fabric that allows users to select records from a table and automatically generate the corresponding INSERT statements. I believe this capability would be particularly valuable for teams using Fabric to manage configuration-driven solutions where tables contain metadata and application settings that must remain synchronized across environments. Thank you for considering this idea.
Support Outbound Mirroring from Fabric Warehouse to External SQL Server
HI Team I would like to propose a feature request for Microsoft Fabric: Outbound Mirroring (Reverse Mirroring) from a Fabric Warehouse to external targets, specifically SQL Server. Currently, Fabric Mirroring is a fantastic inbound feature that replicates data from external sources (like SQL Server, Azure SQL, and Snowflake) into OneLake. However, there is no native, low-latency way to mirror data out of a Fabric Warehouse back into an operational SQL Server instance. Why this is needed: While Fabric excels as a centralized analytical lakehouse, many organizations still rely on traditional SQL Server databases to power operational systems, legacy applications, and real-time transactional workflows. When analytical insights or aggregated data are generated inside a Fabric Warehouse, getting that data back into an operational SQL Server requires building and maintaining manual Data Factory pipelines, Dataflows, or custom PySpark notebooks. Proposed Solution: Introduce an outbound mirroring capability. This would allow users to select a Fabric Warehouse table (or view) and automatically stream or replicate changes down to a designated on-premises or cloud-based SQL Server instance with minimal configuration and latency. I believe this would bridge the gap between operational databases and Fabric's analytical environment, making Fabric an even more flexible centerpiece for hybrid data architectures. I would love to hear thoughts from the community or if others face similar architecture challenges!
Fabric Copy Jobs desperately need basic editability after creation.
Requiring users to recreate an entire Copy Job just to change something as fundamental as the source connection or connection URL is unnecessarily restrictive and creates significant maintenance overhead. A Copy Job should allow users to: Change the source connection Change the destination connection Edit connection details Repoint a job to a replacement connection Preserve existing mappings, scheduling, and other configuration when changing connections Having to rebuild a working job because one connection property needs to change makes Copy Jobs much less useful for production data workflows. Please add the ability to edit or replace connections on an existing Copy Job.
