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vamshikrishna20's avatar
vamshikrishna20
Icon for Helper III rankHelper III
6 months ago
Solved

Chatgpt like Model in Power BI

Hello,  We are trying to work on AI use case with Power BI and facing difficulties doing that. our problem statement is -    we have a Power BI Report which is having metadata of 10 oracle table...
  • MohdZaid_'s avatar
    6 months ago

    Hey vamshikrishna20  ,

     

    First, the Reality

    What you’re trying to do cannot be done directly inside Power BI alone.

    Power BI is great at:

    • Showing data
    • Modeling data
    • Creating dashboards

    But it is not designed to read unstructured documents like PDFs and “understand” them or compare them intelligently with your semantic model.

    That’s why importing the Oracle release notes PDF into Power BI didn’t work. It can extract text, but it cannot interpret meaning.

     

    What You Actually Need

    Your requirement is:

    When Oracle releases new feature notes, automatically check if any of our 10 Oracle tables in Power BI are impacted.

    To do this, you need something that can:

    1. Read the Oracle release notes (PDF)
    2. Understand which tables or columns are mentioned
    3. Compare that with your Power BI semantic model
    4. Tell you what is impacted

    This requires an AI/LLM layer outside Power BI.

     

    Simple Working Solution (Practical Approach)

    Here’s how you can realistically implement it:

    Step 1 – Use an AI Service to Read Release Notes

    Use something like:

    • Azure OpenAI
    • OpenAI API
    • Any enterprise LLM tool

    This AI will:

    • Read the Oracle release notes PDF
    • Extract table names, column changes, deprecations, etc.
    • Convert them into structured output

     

    Step 2 – Extract Your Power BI Model Metadata

    From Power BI, you can export:

    • Table names
    • Column names
    • Relationships

    This can be done using:

    • XMLA endpoint
    • Tabular Editor
    • Power BI REST API

    Store this metadata somewhere (SQL table, Excel, SharePoint, etc.).

     

    Step 3 – Compare Using AI

    Now send both things to the AI:

    • Oracle release notes summary
    • Your Power BI model metadata

    Ask it:

    “Tell me which of my tables are impacted and what kind of impact it is.”

    The AI will return a structured response.

     

    Step 4 – Show Results in Power BI

    Store the AI output in:

    • SQL
    • Excel
    • SharePoint
    • Fabric Lakehouse

    Then simply build a Power BI dashboard that shows:

    | Table | Impact Type | Severity | Action Required |

    Now Power BI is just displaying the results — not doing the AI work.

     

    If You Are Using Microsoft Stack

    If your company uses Microsoft ecosystem, the best enterprise approach is:

    • Microsoft Fabric
    • Azure OpenAI Service

    This makes integration much smoother and secure.

     

    If it solved your issue, feel free to mark it as the solution so others can benefit too.

     

    Thanks for being part of the community.