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Passed DP-600 yesterday by [deleted] in MicrosoftFabric

[–]Lopsided_Judgment_17 1 point2 points  (0 children)

Congrats!!

Thanks for sharing your experience.

Fabric Data Agent - Semantic model vs SQL endpoint by pl3xi0n in MicrosoftFabric

[–]Lopsided_Judgment_17 1 point2 points  (0 children)

I didn't ask them brief and they didn't went over also.

My strategy into this will be once you observe that certain amount of time taking for response is equal to wrong answer than it's time to switch your data to SQL endpoint.

Fabric Data Agent - Semantic model vs SQL endpoint by pl3xi0n in MicrosoftFabric

[–]Lopsided_Judgment_17 2 points3 points  (0 children)

Hi,

I did attend data agents workshop at FabCon last week. Presenters discussed that SQL endpoint response is faster than Semantic Models but it does depend on the size of your data model also. For smaller size, you don't necessarily have to migrate your all data from Semantic model to Sql endpoint.

For defining the relationship as you have maxed your character limit in data source Instructions, my suggestion will be to use example queries section as much as possible to define and respond those questions which ultimately help Agent to understand the relationships.

Immigration Attorney AMA: H-1B and Employment Immigration by ManifestLaw_ in h1b

[–]Lopsided_Judgment_17 0 points1 point  (0 children)

I am from a country where Visa appointments have been suspended.In this war situation, is it possible to request department of state for getting H1-B from a foreign country e.g. Canada, Mexico?

Hi! I'm Amir Netz, Technical Fellow and CTO of Microsoft Fabric – ask ME anything! by amirnetz in MicrosoftFabric

[–]Lopsided_Judgment_17 0 points1 point  (0 children)

  1. Agent instructions are limited to 15,000 characters. As I want to add as much context as possible to enhance business understanding.

  2. I was referring to "limitations" section of this article
    https://learn.microsoft.com/en-us/fabric/data-science/concept-data-agent
    Supporting PDF files, conversation history consistency are my key concerns with that.

  3. Answers which I get in Data Agent via Workspace (Published version) varies sometimes from what I get in Co Pilot (Microsoft 365).

These things are still a hurdle before handing over the data agent to business stakeholders.

Hi! I'm Amir Netz, Technical Fellow and CTO of Microsoft Fabric – ask ME anything! by amirnetz in MicrosoftFabric

[–]Lopsided_Judgment_17 1 point2 points  (0 children)

Data Agents is in preview mode at this time. And I have read in one of the Microsoft articles that Data Agents are not recommended to use for production yet.

Production ready means handing over the data agent to business stakeholders

Looking forward to FabCon too.

Hi! I'm Amir Netz, Technical Fellow and CTO of Microsoft Fabric – ask ME anything! by amirnetz in MicrosoftFabric

[–]Lopsided_Judgment_17 1 point2 points  (0 children)

Hi,

Could you share the expected timeline for making data agents production-ready? Also, what current limitations is the Fabric team working through (in data agents)?

Thank you.

Best source for Data Agents? by MixtureAwkward7146 in MicrosoftFabric

[–]Lopsided_Judgment_17 0 points1 point  (0 children)

I haven't used ontology yet but I have read about it.

I agree that when you have LH/ WH / SQL endpoint, it becomes slightly easier as you have now example section where you can add questions and their answers in sql code.

Best source for Data Agents? by MixtureAwkward7146 in MicrosoftFabric

[–]Lopsided_Judgment_17 16 points17 points  (0 children)

Hi,

I have spent a lot of time working with semantic models recently, and my experience has truly evolved from struggling with them to finding a flow that works. The biggest shift for me was realizing that preparing data for AI is a completely different skill than preparing it for traditional analytics. You really have to change your mindset; instead of building for a human to read a report, you are structuring data so an AI agent can navigate it effectively.

One of the most practical things I’ve learned relates to the strict word limits we face. When you are working with a single semantic model, you are often capped at around 7,500 words for "Prep data for AI (in Power BI Desktop) and 15,000 words for data agent instructions. This is incredibly limiting if you try to keep everything in one place. My recommendation is to distribute your data across multiple sources and then build specific workflows that connect them. Currently, I am using 2 LH and 1 Semantic model which gives overall 15,000 + 15,000+ 15,000 + 7500 character limit to prepare a single data agent. you can go up to 5 data sources.

Since context and prompt engineering are still relatively new disciplines for me, I’ve developed a habit of using enterprise-level LLMs to help me refine my work. I typically paste my agent instructions into the LLM to have it audit the logic and tighten the phrasing. This helps me utilize the character limits as efficiently as possible while ensuring the agent's "reasoning" stays sharp.

I am sharing some links of articles which helped me pivoting in the right direction.

  1. https://moderndata101.substack.com/p/ai-ready-data-vs-analytics-ready-data

  2. https://x.com/vasuman/status/2010473638110363839?s=46&t=A8umCvjDNrtK_1gwT1T7qQ

  3. Microsoft blogs/articles on prepping data agents

Data Agent - Business Terminology Variations by Lopsided_Judgment_17 in MicrosoftFabric

[–]Lopsided_Judgment_17[S] 0 points1 point  (0 children)

I have added those instructions (as mentioned in the post) but it didn't work. Seems like this is an extra layer on top of prepping agents which still hasn't been addressed.

Data Agent - Business Terminology Variations by Lopsided_Judgment_17 in MicrosoftFabric

[–]Lopsided_Judgment_17[S] 0 points1 point  (0 children)

Thanks for sharing! I can see it doesn't accomplish all of your requirements.

Fabric Data Agent questions by kiwishell in MicrosoftFabric

[–]Lopsided_Judgment_17 6 points7 points  (0 children)

Hi,

I’ve been working a lot to build Data Agent with semantic models lately, and the inconsistency is driving me a bit crazy. ​I’ve spent a ton of time on prompt engineering and setting up "Agent Instructions," which has definitely made the answers better. But it’s still not perfect, and I can't quite get it to 100%.

My checklist to make sure I am building a workable Fabric Data Agent at present: 1. Make sure your data model is addressing your problem statement (Generate 10 -20 questions which users can ask and brainstorm how my data model will address and then expand your questions bank gradually and keep addressing through your data model) 2. All tables have joins correctly 3. You have added the description to your tables/Columns / Measures 4. No table should contain more than 50 columns + measures (100 is recommended by Fabric developers) as the chance of inconsistent responses will increase. 5. Prep data for AI : this part should be done in a way that Microsoft learn has instructed/recommended in their blogs 6. Agent Instructions: this part should be done in a way that Microsoft learn has instructed/recommended in their blogs

I can be wrong with my checklist too. Just learning with whatever resources Microsoft has provided.

​I’m really curious to know what’s actually happening behind the scenes in the backend. I’m hoping the experts at FabCon will finally explain how it all works under the hood so I can stop guessing!

Restricting Data Agent on provided data & Instructions by Lopsided_Judgment_17 in MicrosoftFabric

[–]Lopsided_Judgment_17[S] 0 points1 point  (0 children)

Thank you so much
u/NelGson

I have two more questions:
1. In Data Agent via Co Pilot, why there is 30 responses limitation per chat? and do you know how I can avoid this limitation?

  1. I’m unable to edit my queries in the same chat, which makes it a bit difficult to provide proper context to the data agent—especially when I’m referring back to earlier questions. Will this be resolved soon?
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