Fabric Data Agent: “Query cancelled” on aggregations
Good evening, I’m trying to build a Data Agent for my organization, even though the feature is still in preview. Its source is an ontology. I’m currently working with only six tables, but they are very large. I’m having an issue when asking the Data Agent questions that require grouping and aggregation, such as COUNT or SUM. In those cases, I often get the following error: "Query cancelled by upstream caller Status Code: Cancelled" The agent suggests that this may be caused by the amount of resources required by the query, which seems plausible. I also tried using smaller tables in the ontology. This improved things somewhat, and some queries now work, but aggregations are still extremely slow and I still frequently receive the same error. Is this expected behavior with large ontologies and aggregation queries, or could there be some configuration or setting that needs to be changed? Is there anything I can do to improve the performance of GROUP BY, COUNT, and SUM queries over an ontology-backed Data Agent? EDIT: I also found the following error in one of the question's execution log: 'The request was canceled due to the configured HttpClient.Timeout of 300 seconds elapsing.'
Fabric Data Agent chat error: “The natural language query could not be processed” (Ontology source)
Hi all, I’m having a persistent issue with Fabric Data Agent when using an Ontology as the data source. In the chat, even very simple natural language questions fail with: “The request is invalid. The natural language query could not be processed. Please rephrase your query and try again.” RAID examples: db24d651-d4f8-4dd9-8fcb-bab105ee68eb, bfb8cd2a-676a-40a0-9c91-f36ca250ff07. What I already validated: Ontology and graph are created correctly. Relationships exist and are active. Manual graph queries execute successfully. The issue happens in chat NL queries (NL-to-GQL translation), even with minimal prompts. I recreated the Data Agent from scratch, same behavior. So this looks like a chat/NL parser issue rather than a data or graph execution issue. Has anyone found a reliable workaround, or is this a known service-side issue in preview? Any guidance from Microsoft team would be very helpful. Thanks!A Typo when collapsed left pane in the Graph (Korean)
Hi Team, When I collapsed left-hand components pane in the Graph, I noticed the title was displayed upside down. That should be rotated as follows: Do you have any other thoughts? I will submit a support ticket to support engineer team. https://learn.microsoft.com/en-us/power-bi/support/create-support-ticket Korean English Thanks, HongLet Fabric Data Agent ontology inherit RLS from Semantic Model roles instead of OneLake Security
I'm building a Fabric Data Agent with an ontology on top of a Lakehouse (Customer 360 style model — dimension and fact tables). I also have a Power BI semantic model over the same data with a DAX RLS role already defined (e.g., restricting a "Germany" role to rows for that region). I expected the ontology/Data Agent to honor that semantic model role when a user with the role queries it. Instead, I found that the ontology queries the Lakehouse directly via a graph engine (GQL), and semantic model DAX RLS only applies within the scope of that semantic model — it has no effect on the ontology path. The only way to get row-level filtering enforced there is OneLake Security (data access roles), which requires defining access — including RLS predicates — separately, per table/folder, in the "Manage OneLake security" experience. The problem: This means the same business rule ("this role sees only Germany rows") has to be defined and maintained twice, in two different places, using two different mechanisms: Once as a DAX RLS role in the semantic model (for Power BI reports) Once as OneLake Security data access roles, configured per table, for the ontology/Data Agent path For a model with many related tables (dimensions + facts), this means recreating the same predicate across every table individually in OneLake Security, rather than defining the rule once at the role level and having it apply consistently across all related tables — the way a single semantic model role does. What I'd like to see: I'd prefer that semantic model roles (and their RLS/CLS definitions) can be inherited by, or reused in, the ontology — so one role definition governs both the semantic model and the Data Agent/ontology layer, instead of maintaining a parallel, per-table configuration in OneLake Security. Today it feels like there's no single source of truth for "who sees what" when a Lakehouse is consumed through multiple paths (Power BI vs. Data Agent). Questions for the community/product team: Is there a supported way today to have the ontology consume a semantic model as its data source (rather than Lakehouse tables directly), so DAX RLS is respected end-to-end? Is unifying RLS definition across semantic model and OneLake Security on the roadmap, or is the expectation that these stay as two independently maintained layers? If OneLake Security is meant to be the single enforcement layer going forward, is there a way to define a role once and have it apply across a set of related tables (dimensions + facts) rather than configuring RLS per table? Any guidance — or confirmation this is a known gap — would be appreciated. My Goal is to achieve RLS for Data Agents without having to define rules for each Table which what the Role DAX in Semantic Model offer .A Typo regarding Edge in the graph model (Korean)
Hi Team, When I tried to create a graph model, I noticed a typo about Edge in the left pane: “가장자리”. In the top toolbar, it is displayed as “에지”(Edge). So, that should be “에지”. I will submit a support ticket to support engineer team. https://learn.microsoft.com/en-us/power-bi/support/create-support-ticket Korean English Thanks, Hong
Data Agent gives correct GQL Query but is unable to give output
Hi All, I have a Data Agent connected to a Graph data source that keeps giving error: I'm unable to directly retrieve the data due to a technical issue translating the request to a graph query. However, here is the correct GQL query you can use to get .... The GQL query provided by the Data Agent works perfectly on the Graph instance but the Data Agent is not giving the output. Not sure what is the exact error and where can I see to troubleshoot it. Both Data Agent and Graph are in same workspace (even same folder for that matter).
Fabric Graph - Query Set - REST API - Create GraphQuerySet
Hi, I am following Create Graph Query Set (and Graph QuerySet definition) but failing to successfully create a Fabric Graph query set - I have tried many variations but invariably any error messaging is ambiguous: { "status": "Failed", "createdTimeUtc": <datetime-string>, "lastUpdatedTimeUtc": <datetime-string>, "percentComplete": None, "error": { "errorCode": "Unknown", "message": "unknown error", "isRetriable": False } } I can successfully create an 'empty' query set (with a payload of: {"folderId": <folder_id>, "displayName": <queryset_name>, "description": ""}) - but issues seem to arise when including a "definition" object. (N.B. I am following the same pattern I have successfully used for Semantic Models, Reports and now Graph Models.) Is this endpoint fully implemented (errors and all)? Thanks!Fabric Data Agent on Ontology Fails for Simple and Multi‑Entity Queries (GROUP BY/Aggregation Error)
Hi, I’ve created a Fabric Data Agent using an Ontology as the data source, and I’m encountering consistent failures even when asking simple questions related to a single entity. Queries that span or join multiple entities also fail. Below are the details and the error output. Issue Summary When I ask a basic question (even involving only one entity), the agent returns an error. For multi-entity questions, it fails with the same pattern. The error indicates that the generated Ontology query includes invalid aggregation or grouping logic. Specifically, a field is referenced without being part of the GROUP BY clause or wrapped in an aggregation function. The underlying generated query seems to have a syntax or grouping issue and cannot execute. Query Output: Failed to execute step (RAID: 36eb1c04-9e56-4998-89ac-a9a56919482d). Error: Failed to execute Ontology query with error: "The query is invalid. Reason: BadRequest. Resource: Graph query (graphModelId=9231e6f0-87b9-44b4-9a36-5ddbe39b8d78). InternalCode: 42000. Message: syntax error or access rule violation. Cause: data exception; The identifier node_production_plant.plant_id cannot be used, as it is neither part of the GROUP BY nor an aggregation." I have already enabled "Support GROUP BY in GQL" in the Data Agent instructions. What I need help with: Has anyone seen similar Ontology-based Data Agent failures related to GROUP BY or aggregation? Is this a known limitation or bug when using Fabric Data Agent on Ontology models? Any best practices or modeling patterns to avoid such query-generation errors? Are there known workarounds to ensure the agent produces valid Ontology queries? I can share more examples or screenshots if needed. Thanks in advance for any guidance!Excessive CU usage in Fabric IQ
I’m running a tiny PoC with Fabric IQ and hitting a bottleneck with capacity consumption. The setup is super simple: Capacity: F4 Data: 2 tables from Lakehouse. A "Sale" fact table with 2k rows and a "Salesperson" dimension with 25 records. Ontology: 2 nodes (Sale and Salesperson) and 1 property. Data agent: connected exclusively to the ontology. I asked the Data Agent exactly 10 questions, and my capacity went straight into background throttling. Looking at the metrics, 90% of the CUs were swallowed by GraphIndex (Graph General Operations). Is it normal for such a small dataset to trigger this much usage? Has anyone else seen this or found a way to optimize it? Attached the screenshot of the spike. Before: After 10 prompts: Any tips?
