Introduction
The world of data consumption is rapidly evolving. Static dashboards and canned reports no longer meet the growing demand for real-time, personalized insights. Enter Microsoft Fabric Copilot, a powerful AI-driven assistant that transforms how users interact with data bringing conversational analytics to the forefront.
This blog explores how organizations can shift from static BI reports to dynamic, AI-powered conversations using Copilot Bots in Microsoft Fabric, detailing the architecture, components, setup, and practical use cases.
KEY SHIFTS: Static Report to Conversational Report:
Understanding Conversational Analytics in Fabric
Conversational analytics empowers users to query data in plain language, without needing deep knowledge of report structures or complex formulas. Microsoft Fabric Copilot brings this capability to life by leveraging generative AI, the Power BI semantic model, and Microsoft’s robust language understanding stack.
What Makes It Conversational?
- Natural Language Interface: Instead of building filters, slicers, or DAX formulas, users can simply type questions in plain language—for example: “Show me total sales by region for this quarter.” This lowers the technical barrier and makes data exploration accessible to everyone. Multi-language support is evolving, which could further enable users to ask questions in their own preferred language.
- AI Interpretation: Copilot translates queries into semantic understanding—meaning it recognizes the intent behind a question and maps it to the underlying data model, so users don’t have to worry about technical query syntax.
- Context-Aware Suggestions: Copilot suggests follow-up questions or insights, making exploration continuous.
- Personalized Answers: Responses adapt to user roles, preferences, and access controls.
Architectural Overview:
SETUP & IMPLEMENTATION: Enabling Copilot for Conversational Analytics in Microsoft Fabric
To successfully transition from static reporting to conversational analytics, it’s essential to set up the foundational components that empower Microsoft Copilot to deliver accurate, AI-generated insights. Below are the key steps to prepare your environment:
Step 1: Have the Correct Data in Microsoft Fabric
Conversational experiences are only as good as the underlying semantic model. Ensure your Power BI dataset is optimized for natural language queries by:
- Using clear and descriptive table/column names (avoid technical jargon or acronyms).
- Defining data categories (e.g., location, time, currency) to help Copilot interpret fields correctly.
- Establishing proper relationships and hierarchies within your model.
- Adding descriptions, synonyms, and KPIs for enhanced context awareness.
NOTE: Please refer the below link to Optimize the semantic model for copilot use
Optimize your semantic model for Copilot in Power BI – Power BI | Microsoft Learn
Step 2: Enable Copilot in Microsoft Fabric
Ensure the following prerequisites are in place to activate Copilot features:
- Microsoft Fabric is enabled for your Azure tenant.
- You’re using a Power BI Premium workspace (Copilot requires premium capacity).
- Copilot is turned on in the Fabric Admin Portal:
- Navigate to Admin Portal → Tenant Settings → Copilot and AI Features
- Enable for selected security groups or the entire organization.
NOTE: Please refer below link How to Enable Copilot in Microsoft Fabric
Enable Copilot in Fabric – Microsoft Fabric | Microsoft Learn
Step 3: Interact with Copilot in Power BI
Once enabled, you can start using Copilot within Power BI:
- Open an existing or new Power BI report.
- Click on the Copilot icon (robot symbol) from the top menu.
- Begin typing questions like:
- “Show monthly sales trend for the past year
- What are the top 5 profitable products?
- What are the top 5 profitable products?
Copilot will respond with visual summaries, suggestions, or follow-up questions to refine the output.
Step 4: Secure and Govern Your Environment
Maintaining trust in AI-driven insights requires sound data governance:
- Implement Row-Level Security (RLS) to ensure users only see data they’re authorized to access.
- Use Microsoft Purview to classify data, track lineage, and monitor access.
- Regularly audit Copilot usage to identify adoption trends and troubleshoot issues.
Step 5: Empower Users Through Training & Guidance
To drive adoption and maximize value:
- Train users on how to frame effective questions (e.g., “sales by product category” vs. “revenue breakdown”).
- Provide predefined prompts and example questions in the report or dashboard.
- Encourage feedback loops to improve the data model and address gaps in understanding.
Key Benefits of Conversational Analytics with Copilots in Microsoft Fabric
Real Time Use Cases
Example 1
Prompt: User asking the What is the OEE % Of Factory Alpha?
Response: The OEE % of factory Alpha is 80.49%
Example 2
Prompt: Show me the weekly Average OEE for Factory Gamma in the month of November.
Learn about Power BI Copilot — Explore Microsoft’s official documentation on Power BI Copilot to see its capabilities.
Frequently Asked Questions (FAQs) on Conversational Analytics with Copilot
Conversational Analytics utilises a Natural Language Interface, empowering users to type questions in plain language instead of relying on filters, slicers, or technical formulas like DAX. This approach lowers the technical barrier and makes data exploration accessible to business users across departments, regardless of their technical expertise.
Copilot uses Generative AI and AI Interpretation to translate user queries into semantic understanding. This means Copilot recognises the intent behind the question (e.g., “Show me total sales by region for this quarter”) and accurately maps that intent to the underlying Power BI semantic model, eliminating the need for users to worry about technical query syntax.
To activate Copilot, organisations must first ensure the following prerequisites are met: Microsoft Fabric is enabled for the Azure tenant, and they are using a Power BI Premium workspace (as Copilot requires premium capacity). The feature must then be explicitly turned on within the Fabric Admin Portal under Tenant Settings → Copilot and AI Features.
Conversational experiences are only as effective as the underlying semantic model they employ. To optimise the data, organisations must use clear and descriptive table and column names (avoiding technical jargon), define data categories (such as location, time, or currency), establish proper relationships, and add descriptions, synonyms, and KPIs for enhanced context awareness.
Maintaining trust requires sound data governance. Organisations must implement Row-Level Security (RLS) to ensure users only see data they are authorised to access. Additionally, they should leverage Microsoft Purview to classify data, track lineage, and monitor access, ensuring secure and compliant access to sensitive information.
The shift to conversational analytics delivers several major benefits, including: Real-Time Insights from live data, Reduced Report Backlog (as analysts spend less time building static reports), Improved Accessibility, and Accelerated Decision-Making due to faster access to information.
