The data preview in the Results section of a SQL query (in either a warehouse or lakehouse) is very difficult to read as it is currently set up. It would be massively improved by implementing the following: Show the total row count at the bottom of the Results rather than just showing the row preview limit (10,000) if the actual row count goes beyond this Ideally, this would show something like Columns: 4  Rows: 56012  Rows Displayed: 10000 Allow columns in the Results to be dragged wider so it's possible to read the full column names and data As far as I can see, there's currently no way to do this in Fabric ... View more

Hello Microsoft Team,   Currently, Power Automate offers a trigger for Power BI dataflow refresh completion, but there is no native trigger for Power BI semantic model (dataset) refresh completion. According to community and documentation, this gap forces users to rely either on data‑driven alerts, which cannot detect failure states, or REST API polling, which requires Premium HTTP actions.   Many business workflows depend on knowing whether a dataset refresh succeeded or failed, especially when downstream automation or data quality processes rely on up‑to‑date semantic model data.   I would like to request a new built‑in trigger:  “When a Power BI semantic model (dataset) refresh completes” with outputs such as:   Refresh status (Succeeded / Failed) Error details Start and end time Workspace ID and Dataset ID This would eliminate the need for complex REST API workarounds and significantly improve automation reliability for Power BI + Power Automate users. Thank you. ... View more

Since the foundational format for one lake is the delta file format, why has no SQL syntax for adding comments to both Tables and Columns within tables.   With Generative AI, it more important than ever to tag tables and columns with descriptions.   Below is the syntax supported by delta files for tables.   COMMENT ON TABLE table_name IS 'your desired comment';'   Below is the syntax supported by delta files for columns.   ALTER TABLE table_name ALTER COLUMN column_name COMMENT 'your desired column comment';   Please see vendors like Snowflake (warehousing) and PostgreSQL (database) that have implemented this syntax.  It is alot cleaner than the stored procedure syntax in Fabric SQL database.  Below is the comment on a table.   EXEC sp_addextendedproperty @name = N'MS_Description', @value = N'This table contains information about library books on loan, including their ID, book ID, member ID, borrow date, due date, and return date.', @level0type = N'SCHEMA', @level0name = N'data_raw', @level1type = N'TABLE', @level1name = N'loans01';   Additionally, a comment on a column. EXEC sp_addextendedproperty @name = N'MS_Description', @value = N'LoanID', @level0type = N'SCHEMA', @level0name = N'data_raw', @level1type = N'TABLE', @level1name = N'loans01', @level2type = N'COLUMN', @level2name = N'The primary key for the loans table.';   ... View more

The business needs Excel to perform on Fabric   The Problem: Unoptimized Capacity Consumption and Performance Bottlenecks While Excel's live connection to Fabric Semantic Models is a key feature, it currently presents a significant challenge for enterprise-level deployments, primarily related to performance and the unoptimized use of Fabric capacity. The core issue is that the current connection method, which relies on the XMLA endpoint and MDX query translation, leads to:  * Excessive Capacity Consumption: Every user interaction—from dragging a field to applying a filter—generates an independent, and often verbose, MDX query that is translated and executed. This constant, unoptimized querying on a per-user, per-click basis results in a high number of interactive queries, which are the most expensive type in Fabric capacity.  * Poor User Performance: As a result of the unoptimized queries, users experience frustratingly slow response times. A simple action that should be near-instantaneous can take several seconds to complete, especially with complex semantic models and multiple concurrent users. This degrades the user experience and can lead to a lack of trust in the centralized data model. The Proposed Enhancement: A Modern, Optimized Connection Layer We request the development of a new, modernized connection layer for Excel that is purpose-built for Fabric Semantic Models. This would move beyond the legacy MDX translation approach and provide a more intelligent and efficient way for Excel to interact with the service. Key features of this enhanced connection layer should include:  * Smart Query Batching: Implement a mechanism to intelligently batch multiple user actions into a single, optimized query to the Fabric service. This would significantly reduce the number of interactive queries, lowering capacity consumption and improving performance.  * Native DAX Support: Instead of translating MDX to DAX on the server, allow Excel to generate optimized DAX queries directly from the client. This would eliminate a performance bottleneck and ensure that the queries are written in a way that best leverages the semantic model's structure.  * Improved User Experience: A faster, more responsive connection would dramatically improve the user experience, encouraging broader adoption of Fabric as the go-to platform for data analysis in conjunction with Excel. Business Impact: Unlocking True Enterprise Scalability This enhancement is not just a "nice-to-have"; it is critical for unlocking the true enterprise scalability of Microsoft Fabric. A modern, performant connection between the world's most popular spreadsheet tool and Microsoft's unified data platform would:  * Reduce TCO: By consuming capacity more efficiently, organizations can get more value from their Fabric investment and manage costs more effectively.  * Boost Productivity & Trust: Faster performance means business users can work more efficiently, building trust in the centralized data model and reducing reliance on manual, ad-hoc data sources.  * Strengthen the Microsoft Ecosystem: This would further cement the powerful synergy between Fabric and Office, demonstrating a seamless and high-performance experience for the millions of users who rely on both products daily. Summary: Everyone agrees, Excel is not going away. Optimizing Excel's connectivity to Fabric Semantic Models for capacity and performance is essential. We urge the Fabric team to prioritize the development of a modern, efficient connection layer that will not only solve current user frustrations but also enable organizations to confidently scale their analytics solutions. Fabric has gone miles beyond a reporting tool as it has evolved into Fabric, these changes fully fit within the scope of providing a robust end to end Analytics platform.     ... View more

Problem When developing or operating Warehouse‑backed models, we often need small, surgical data fixes - e.g., correcting an erroneous valid_to_dt in an SCD2 dimension or updating a junk‑dimension attribute. In SQL Server/SSMS, the “Edit Top N Rows” grid makes this fast and safe. Fabric Warehouses currently lack a GUI row editor, pushing teams to external tools (e.g., DataGrip) or ad‑hoc DML scripts. This creates friction, slows incident resolution, and fragments tooling—even though Warehouses already support full DML via T‑SQL.   Proposal Provide a first‑class “Edit Top N Rows” experience for Warehouse tables: Fabric Portal: grid editor with inline add/edit/delete, filter, and commit/rollback. SSMS / VS Code: enable the same grid or a lightweight editor with “generate DML” preview. Respect Warehouse permissions/RLS; optionally log changes via SQL Audit Logs and take a Time‑Travel snapshot for quick rollback. Why this matters Speeds data quality hotfixes, removes the need for competitors’ tools, and lets us fully standardize on VS Code + SSMS + Fabric while retaining governance and safety. ... View more

With the rising adoption of Multi-Factor Authentication (MFA) across our organization and industry best practices, we are seeking a more robust and streamlined authentication method for connecting Power BI to Snowflake. Currently, Power BI primarily relies on username/password or OAuth 2.0 via Microsoft Entra ID. While these methods are functional, they can become cumbersome and less secure in MFA-enabled environments. We propose the implementation of RSA key pair authentication for Snowflake connections within Power BI. ... View more

A Lakehouse Collation setting showing case sensitive vs non-case sensitive should be added to the exisitng lakehouse settings in Microsoft Fabric.  For years i've been able to change collations on a database on on-prem SQL and am able to re-populate those data tables to reflect the new collation moving forward.  This should be an option in Microsoft Fabric in the lakehouse settings which should allow me to change a collation on an existing Lakehouse without having to create a brand new Lakehouse and have to completely recreate anything in it's lineage such as semantic models, reports, etc.  Seems like we could do this for the last 20+ years in SQL and should be able to do this using a Lakehouse easily as well. ... View more

When connecting to a semantic model currently, we have to use the workspace/lakehouse/warehouse unique id and semantic model unique id in order to analyze that semantic model.  Instead of using those unique ids attached to a very specific semantic model we should be able to have the ability to customize those unique ids to a static customizable user friendly names for ease of use and the best customer experience.  Currently if I want to analyze a semantic model in Microsoft Excel or another methodology, if I have to connect to that model with the unique workspace/warehouse/lakehouse id and unique semantic model id, why can't I use the user facing workspace name, lakehouse name and semantic model name?  Why are we using GUIDs in 2025?   Additionally, if I have a new model that needs to replace an existing model, I should be able to replace or rename that model to the existing model name and it should inherit the current model's lineage vs recreating and redeploying all the associated lineage items to the new model.  This would save so much development time it's ridiculous that there is no solution for this currently. ... View more

Currently I need to use Tabular Editor to make modifications to the collation assigned with any semantic models I create in Microsoft Fabric.  These collations appear to be a random bug and do not always inherit my lakehouse collation.  This causes issues when my users/customers try to analyze a semantic model inside of Microsoft Excel and try to filter data for a specific data value in the model that is case sensitive.  A button should be added to the semantic models settings that turns case sensitivity on or off.  As a work around, I am currently using Tabular editor to modify a semantic model and deploy a copy to Fabric.  This does not allow me to modify the existing semantic model, but create a new semantic model with the collation I want.  This should be an easy add/fix that should already be in Microsoft Fabric since it's kind of already in a 3rd party tool. ... View more

Hi, working with warehouses often I need to view the dependencies between tables and views (but also with stored procedures and so on). Generally I query the sys.sql_expression_dependencies view, but I should be more useful a visual feature as f.e. that one of SSMS:     Work better to work less. Thanks! ... View more

Currently Dataverse is not available to use as a real-time data source. Adding Dataverse will allow dashboards for real-time views of Dataverse and other Power Platform data natively. Real-time dashboards previously supported dataverse data with power automate pushing to streaming datasets. This capability is now deprecated but not replaced.   ... View more

Based on https://community.fabric.microsoft.com/t5/Data-Engineering/Creating-a-Primary-Key-for-Lakehouse-Table/m-p/4742452#M10401 and based on error message that I'm receiving when creating keys from notebook (Table constraints (Primary and Foreign key) are not supported in V2 Datasource tables) seems that primary and foreign keys are not supported in Lakehouse. I believe that support for keys would be very useful and beneficial. The thing is that through the SQL analytics endpoint you can create them which is confusing so I contacted Microsoft to see what is the status and the response was: You're absolutely right—Microsoft Fabric currently has limited support for table constraints like primary and foreign keys. Here’s a summary of the current behavior and limitations: What Works: Primary keys can be defined only via the SQL Analytics Endpoint, using syntax like: ALTER TABLE MyTable ADD CONSTRAINT PK_MyTable PRIMARY KEY NONCLUSTERED (id) NOT ENFORCED; This allows you to register metadata constraints, which can be useful for documentation or downstream tools. Where Primary Keys Are Supported: Fabric SQL Database (distinct from Lakehouse) does support primary keys and foreign keys, similar to Azure SQL Database or SQL Server. However, even in Warehouse or SQL Analytics Endpoint, constraints like PRIMARY KEY, FOREIGN KEY, and UNIQUE are only supported when: NONCLUSTERED NOT ENFORCED Limitations: These constraints are not enforced—they do not prevent duplicates or ensure referential integrity. They are not supported in V2 Datasource tables, which is why attempts from notebooks result in the error: "Table constraints (Primary and Foreign key) are not supported in V2 Datasource table." Foreign keys and unique constraints follow the same pattern: metadata-only, not enforced. Known Issues Duplicate data can still be inserted, even if a primary key is defined. No enforcement during ingestion or transformation—you’ll need to handle integrity checks manually. Metadata APIs may not behave as expected (e.g., JDBC metadata queries may not return constraint info reliably). Microsoft has not officially announced full support for enforced constraints in Lakehouse tables. ... View more

Hello, Currently, Power BI connects to Google Cloud Storage using HMAC credentials, which require manual key management and pose security and scalability challenges. I propose adding support for Workload Identity Federation (WIF) as an authentication method to enhance security, simplify credential management, and align with modern cloud identity practices. Advantages of WIF Authentication Improved Security: WIF eliminates the need for long-lived HMAC keys by using short-lived, automatically rotated tokens via identity providers. No Key Rotation Hassles: Credentials are federated dynamically, removing the need to manually rotate or store HMAC keys. Centralized Identity Management: Integrates with enterprise identity providers, enabling fine-grained access control and auditability. Scalability: Ideal for large-scale deployments where managing static keys becomes impractical. Compliance-Friendly: Supports modern security standards and helps meet compliance requirements for cloud-native environments. Limitations of HMAC Authentication Manual Key Management: Requires storing and rotating static access keys, which increases operational overhead. Security Risks: Static keys are vulnerable to leakage and misuse if not handled securely. Limited Integration: Does not integrate well with identity providers or support federated access models. Audit Complexity: Tracking access and usage is harder compared to federated identity systems. Conclusion Adding WIF support for Google Cloud Storage in Power BI would significantly improve security, reduce administrative burden, and align with best practices for cloud identity management. This enhancement would benefit organizations looking to modernize their data access architecture while maintaining robust governance.   Thanks, Surendhar ... View more

Could Microsoft support SQLMesh project so that they provide good compatibility against Fabric warehouse and lakehouse (via Spark)? Could SqlMesh be added as Fabric native workload to get it as service since this kind of sql modeling functionality with web UI is missing? Add support for Microsoft Fabric · Issue #3374 · TobikoData/sqlmesh ... View more

Dataflows need a way to reference a table as input, do a comparison and perform upserts on through the data destination in a single dataflow. Instead of having to rely on truncate/reload with replace or creating a stored procedure to do upserts on a staged table of changes. ... View more

When provisioning a new Fabric SQL Database, after typing in the name I want, what I get is that name PLUS some random GUID characters. This just seems wrong. Nobody likes to have their stuff renamed. As I understand it by someone from Microsoft in the Fabric Community, this was done to ensure a unique name across the entirety of Microsoft Fabric. It would be nice if that was NOT a requirement. Maybe you can make it like Fabric Warehouses where it is the combination of the Tenant, Workspace, and Data Warehouse name that needs to be unique. ... View more

Hi, it would be very useful to enable taking control of mirrored databases, because if someone leaves the organization, it has to be recreated from scratch. ... View more

Overtime queries ran on a sql end point in a lake house build up in the my queries folder. They have to be individually deleted which can take a lot of time. There should be a way to delete all or highlight an delete multiple queries  ... View more

I’m aware that Lakehouse Git integration in Microsoft Fabric is currently in preview. However, I believe some critical support is missing that would significantly enhance the usability and maturity of this feature.   At the moment, Git integration does not support versioning or tracking of critical Lakehouse objects such as: Tables Views User-defined functions Stored procedures These objects are essential components of any data platform, and not being able to track their definitions in source control limits our ability to: Perform proper code reviews Roll back changes Maintain consistent environments across workspaces Collaborate effectively in larger teams Follow DevSecOps best practices Suggestion: Please extend Git integration in Fabric Lakehouses to include full support for these objects. For example, warehouse git integration supports all of those objects. This enhancement would greatly improve DevOps practices in Fabric and align with modern data engineering workflows. ... View more