How to Create a Tracking Dashboard in Power BI with AI
Trying to build a tracking dashboard in Power BI can feel like a heavy lift, especially if you’re not a full-time data analyst. But with the introduction of AI-powered features, the process is getting significantly easier and faster. This guide will walk you through how to use Power BI's AI capabilities, particularly Copilot, to create a meaningful tracking dashboard from scratch, even if writing DAX formulas isn't your favorite pastime.
Why Use AI to Build a Power BI Dashboard?
Let's be honest - traditionally, building a dashboard in a business intelligence tool like Power BI requires a specific skill set. You need to understand data models, relationships, and the often-intimidating DAX query language. It’s a steep learning curve that keeps many marketing and sales professionals stuck in spreadsheets.
AI changes that dynamic by acting as your co-pilot. Instead of manually dragging and dropping fields and writing formulas, you can describe what you want in plain English. This approach offers several huge advantages:
Speed: What once took hours of meticulous configuration can now be generated in minutes. You can go from a blank canvas to a functional report in a single session.
Accessibility: You don't need a degree in data science to ask, "Show me our monthly revenue trend." AI tools lower the barrier to entry, empowering more people on your team to get answers from data.
Discovery: Sometimes you don't know what you're looking for until you see it. AI can help you quickly prototype different visuals and uncover insights that might have been buried behind complex filters and calculations.
Getting Your Data Ready for AI Analysis
Before you can start building, you need data. Power BI’s AI works best with a clean and well-structured data set. Your data is the foundation of your dashboard, so setting it up correctly is the most important step.
1. Gather Your Key Data Sources
Your tracking dashboard will likely pull from a few different places. Identify where your key performance indicators (KPIs) live. Common sources include:
Excel or Google Sheets: Great for exporting data from platforms that don't have a direct Power BI connector. For example, manual sales logs, content calendars, or ad spend summaries.
CRM Data: Exporting leads, deals, and activities from tools like Salesforce or HubSpot.
Web Analytics: Connecting directly to sources like Google Analytics to pull in traffic, user behavior, and conversion data.
E-commerce Platforms: Tapping into Shopify or similar e-commerce systems for sales, product performance, and customer data.
2. Connect Your Data in Power BI
Once you know where your data lives, you need to bring it into Power BI Desktop. From the "Home" ribbon, click "Get Data" and choose your source. If you’re pulling from multiple sources (like a spreadsheet for ad spend and Google Analytics for website sessions), Power BI can help you link them together.
3. Create a Simple Data Model
You don't need to be an expert here, but having basic relationships defined will make the AI’s job much easier. If you have two tables - one with sales data (identified by ProductID) and another with product details (also containing ProductID) - make sure Power BI knows that the ProductID column connects them. This allows the AI to correctly answer questions like "Show me sales by product category" by correctly joining the information from both tables.
A Step-by-Step Guide: Creating Your Tracking Dashboard with Copilot
Once your data is loaded, it's time to build. The primary AI tool you’ll use for this in Power BI is called Copilot. Think of it as a conversational partner that builds visualizations based on your text prompts.
(Note: Copilot in Microsoft Fabric must be enabled by your organization’s administrator.)
Step 1: Open the Copilot Pane
In Power BI Desktop, look for the "Copilot" button in the ribbon. Clicking it will open a new pane on the right side of your screen where you can start typing your requests.
Step 2: Ask for a New Report Page
The simplest way to start is to ask Copilot to create a whole report page for you. This primes the AI with context and lets it suggest visuals that cover the broad strokes of your data. Try a prompt like:
Create a page to track our key sales and marketing KPIs for the last 90 days.
Copilot will analyze your dataset and generate a page with several relevant charts, like total sales over time, sessions by marketing channel, and top-selling products. It’s an effective way to get an instant first draft.
Step 3: Create and Modify Individual Visuals with Natural Language
From here, you can refine the dashboard by creating new visuals or modifying existing ones. Be clear and specific in your requests. You can point Copilot to an existing chart and ask it to make a change.
Example Prompts for Creating:
"Create a bar chart showing revenue by country."
"Show me the number of website sessions as a line chart over the last 30 days."
"Add a donut chart for leads by status."
"Make a table with our top 10 products by units sold this quarter."
Example Prompts for Modifying:
(After selecting a chart) "Change this to a waterfall chart."
(After selecting a chart) "Add a forecast line extending 3 months into the future."
(After selecting a chart) "Filter this visual to only show data for the 'USA'."
Step 4: Use AI to Summarize Your Data
Beyond creating charts, Copilot can also help you understand them. Once you have a dashboard page, you can ask for a narrative summary of the insights present on the page.
Try this prompt in the Copilot pane:
Summarize the insights on this report page.
Copilot will analyze all the visuals and generate a text summary, pointing out key trends, outliers, and takeaways - for example, "Website traffic saw a significant increase of 25% in the last week, primarily driven by the 'Organic Search' channel." This is an incredibly powerful feature for quickly generating commentary for presentations or weekly reports.
Other Power BI AI Features to Know
Copilot is the star of the show for dashboard creation, but Power BI has other built-in AI tools that can help with deeper analysis.
Smart Narratives
This is a specific visual that automatically generates a text summary of a chart or the entire report page. Unlike the broader Copilot summary, it exists as an interactive textbox within your dashboard that updates automatically as users filter the data.
Q&A Visual
The Q&A visual lets you embed a natural language query box directly into your dashboard. This empowers anyone viewing the report to ask their own follow-up questions about the data, like "What were the total sales for hats?" without needing to modify the report themselves.
Key Influencers
This visual helps you perform root cause analysis. Select a metric you want to analyze (e.g., "Customer Churn"), and the visual will analyze your data columns to determine which factors have the biggest influence on that outcome (e.g., customers are more likely to churn if "User Type" is "Free Trial").
Tips for Getting Better Results from AI
Keep Your Language Simple: Avoid complex jargon. Instead of "Devise a visualization for temporal revenue flow," just say "Show me revenue over time."
Use Your Column Names: If your sales column is named "Total_Revenue," try to use that exact term in your prompt for better accuracy. The AI is smart, but giving it clear signposts helps.
Start Broad, Then Refine: Don't try to build the perfect, hyper-specific chart in one massive prompt. Ask for a basic chart first ("show me sales by category"), then ask follow-up questions to refine it ("now filter for Q2," "sort it in descending order").
Check the Work: AI is a powerful assistant, not an infallible expert. Always glance at the data and chart settings to confirm the visual is showing what you truly asked for.
Final Thoughts
Leveraging AI within Power BI, especially conversational tools like Copilot, transforms dashboard creation from a technical chore into a more intuitive, creative process. It empowers you to explore your sales and marketing data fluidly, generate insights quickly, and build compelling tracking reports without getting bogged down in complex formulas and configuration menus.
While AI features are making complex BI tools easier to use, the process of connecting disparate data sources and navigating a complex interface can still feel like a part of the job you'd rather skip. We created Graphed because we believe getting answers from your data shouldn't require learning an entirely new platform. Our approach is built entirely around natural language, allowing you to connect all your marketing and sales tools in a few clicks and build real-time, interactive dashboards just by describing what you want to see - no setup or configuration required.