Why Most Users Don’t Know About the “Prep Data for AI” Feature in Power BI Desktop
Get Power Bi Ai Ready – Many Power BI users are unaware that the powerful “Prep Data for AI” option exists right inside Power BI Desktop. This feature is the foundation for unlocking cutting-edge AI capabilities like Copilot that transform how reports and insights are generated. If you want to truly harness AI’s power in Power BI, understanding and using this tool is essential. This article will walk you through its detailed steps, practical examples, and how to verify your prep work by testing Copilot’s “Analyze report” and “Analyze data” features.
The Three Essential Steps to Prep Data for AI in Power BI Desktop
The Prep Data for AI process is simple yet powerful and organized into three core areas:
1. AI-Ready Data Schema
The data schema is the structural map of your model—tables, columns, relationships, and measures. To be ready for AI:
- Simplify the schema: Hide unnecessary technical columns and only expose user-centric, business-relevant fields.
- Organize relationships: Use star schema design principles to ensure clear, direct relationships between data tables.
- Name thoughtfully: Use descriptive, concise names for tables and fields to help AI better interpret data.
Example: Hide internal ID columns or audit fields that add noise. Rename ambiguous columns like “Val1” to “Total Sales Amount” for clarity.
2. Verified Answers
Verified answers are a curated list of common or important questions your users might ask Copilot, along with associated visuals. They serve as trusted responses that Copilot can reliably pull to avoid common AI pitfalls like hallucinations or misinterpretations.
- Map questions to visuals: For example, “What was the total revenue last quarter?” maps to a specific revenue card visual.
- Create a verified answers list: Add prioritized questions for your business scenarios.
- Enable precision: This controls Copilot to prefer these visuals and answers over general AI guesses for improved accuracy.
Example: Set verified answers for “Monthly Sales Trend,” “Top 5 Products by Revenue,” and “Customer Churn Rate” so Copilot sources the correct visuals quickly.
3. AI Instructions
These are textual commands or hints embedded into your data model to guide Copilot’s understanding of complex fields, synonyms, or business rules:
- Define synonyms: For example, “revenue” may also be called “sales” or “turnover” in your organization.
- Provide instructions: Explain how certain metrics are calculated or what business context applies.
- Domain expertise: Embed knowledge so Copilot’s responses reflect governance and data accuracy.
Example: Add instructions like “Total sales includes discounts and returns,” or synonyms mapping “Net Profit” to “Earnings.”
Detailed Step-by-Step: How to Use “Prep Data for AI” in Power BI Desktop
- Open Power BI Desktop.
- Go to the “Modeling” tab in the ribbon.
- Click on the “Prep data for AI” button (often found near AI features or Copilot integration).
- Step through the process pane that guides you to optimize schema, add verified answers, and enter AI instructions.
- Save your work and publish the model to Power BI Service to enable full AI integration.
How to Test Copilot After Preparing Your Model for AI
Once your data is prepped, the next step is to verify how well Copilot interacts with your model. Use these features in Power BI Service or Desktop:
Analyze Report
This feature lets Copilot analyze an existing report page and provide insights or suggested visuals based on the data.
- Open the report page you want to test.
- Click the Copilot or AI assistant icon and select “Analyze report.”
- Ask natural language questions like “Explain the sales trends here” or “What are the top drivers of profit?”
- Evaluate the accuracy and relevance of the AI’s narrative and visual suggestions.
Analyze Data
This allows Copilot to answer questions directly about the data model without a report:
- Open the dataset or model view.
- Click the AI or Copilot pane, select “Analyze data.”
- Ask queries such as “Show me monthly revenue by region” or “List top 5 customers by purchase volume.”
- Confirm that the AI understands your schema, verified answers, and instructions effectively.
Additional Power BI AI Updates to Know
Beyond data prep, Microsoft continues to expand Power BI’s AI capabilities:
- Generative AI for report creation: Copilot now builds pages based on single prompts.
- Semantic models integration: Deeper connections with Microsoft Fabric for unified AI access.
- Enhanced anomaly detection: AI-powered alerts embedded in dashboards.
- Conversational Q&A: Natural language processing for live data queries.
Outbound Resources for Further Learning
Visitors looking to dive deeper should explore official Microsoft documentation:
- Prepare your data for AI – Power BI | Microsoft Learn – Comprehensive guide on prepping AI-ready data schemas, instructions, and verified answers.
- Overview of Copilot for Power BI – Understand Copilot’s capabilities and AI integration in Power BI.
Summary: Taking Your First Steps to Get Power BI AI Ready
Getting AI-ready in Power BI isn’t complex, but it requires intentional schema design, carefully created verified answers, and thoughtful AI instructions. Once set up, you can test Copilot confidently using “Analyze report” and “Analyze data” features, ensuring the AI understands your business needs and delivers precise, actionable insights.
By following these detailed steps, you empower your organization with next-generation analytics—fast, accurate, and designed for modern business challenges. It’s not just about using AI; it’s about preparing your data and environment to harness AI’s full potential.
Ai in Power Bi : Create Next Level Reports in Seconds Using the Latest Update
