How to Turn On Underlying Data in Power BI

Seeing the high-level trends in your Power BI dashboards is great, but sometimes you need to dig deeper into the specific numbers behind a chart. Enabling viewers to see the underlying data transforms your reports from static displays into interactive, analytical tools. This article will walk you through exactly how to turn on and use this feature to validate data, answer specific questions, and troubleshoot your visualizations.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

What Exactly Is "Underlying Data" in Power BI?

Simply put, underlying data refers to the individual rows of data that contribute to a specific part of your visualization. Think of it like this: a sales bar chart might show you that you had $50,000 in sales in Canada. That $50,000 is the aggregated total, the summary.

The underlying data is the list of every single transaction that added up to that $50,000. It's the row-level detail that includes the customer's name, the product they bought, the purchase date, and the exact sale amount for each order.

In Power BI, this feature lets you and your report viewers click on a specific data point - like the bar for "Canada" - and see a table of those individual sales records. This is one of the most powerful features for building trust and allowing true data exploration because it provides complete transparency into how your summary numbers are calculated.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Why Viewing Underlying Data is a Game-Changer

Enabling this feature isn't just a "nice-to-have." It serves several critical functions for anyone who creates or consumes data reports. Here’s why it’s so valuable:

• Data Validation and Trust: The number one reason to use this feature is to verify that your data is correct. If a number on a chart seems off, seeing the underlying records is the fastest way to confirm whether the calculation is accurate or if there's an issue with the source data or the filters you've applied. It helps answer the question, "Where did this number come from?"
• Deeper, Ad-Hoc Analysis: High-level metrics often spark new questions. A report might show a sudden sales spike on a specific day. By viewing the underlying data for that day, you can quickly identify if the spike was caused by one massive order from a single client or hundreds of smaller orders from a successful marketing campaign. This takes you from seeing what happened to understanding why.
• Answering Specific Stakeholder Questions: Imagine you're in a meeting sharing a dashboard, and your manager points to a metric and asks, "Can you pull up the list of top 10 clients who contributed to that Q4 revenue number?" Instead of saying, "I'll get back to you," you can click on the Q4 data point, view the underlying data, and sort it by sales amount right there. It turns you into a data hero.
• Troubleshooting and Debugging: Sometimes, visuals don't behave as expected. A count might be too high, or a sum might be too low. Viewing the underlying data helps you instantly see what's being included (or excluded) from the calculation. You might find duplicate rows, incorrect product categorizations, or wrongly-applied filters that you wouldn't have spotted otherwise.

How to Enable "Seeing Records" for Your Report Viewers

As the report author in Power BI Desktop, you have full control over whether your viewers can access the underlying data. This functionality is enabled on a per-visual basis, giving you an excellent level of governance - you might want it enabled for a detail-oriented sales table but disabled for a high-level executive KPI card.

Follow these steps to enable the feature for a specific visual:

1. Select the Visual: First, click on the chart or visual on your report canvas that you want to configure. This will bring up the contextual panes on the right-hand side.
2. Go to the "Format your visual" Pane: On the right, you'll see the "Data" and "Format" panes. Click on the paintbrush icon to open the "Format your visual" options.
3. Expand the "Header icons" Section: Scroll through the list of formatting options until you find "Header icons." Click to expand it. This section controls the icons that appear in the top-right corner of your visual (like the filter icon, focus mode icon, and the "more options" icon).
4. Toggle the "Icons" On: Inside the "Header icons" section, you’ll see another list of toggles for specific icons. Find the one labeled "..." (More options) and make sure the toggle switch next to it is turned to On.

That's it! When this is enabled, the three dots (...) will appear in the visual’s header when users hover over it in the Power BI Service, giving them access to the "Show data point as a table" and "See records" menu options.

An Important Note on Report-Level Export Settings

Beyond just viewing the data inside the report, you might also want users to be able to export it to a CSV file. This is controlled by a separate, report-level setting.

To check this setting:

1. In Power BI Desktop, go to File > Options and settings > Options.
2. Under the "CURRENT FILE" heading, select "Report settings".
3. Scroll down to the "Export data" section.
4. Make sure the option "Allow end users to export both summarized and underlying data from the service or Report Server" is selected.

This setting works in tandem with the visual header icon. If you disable exporting at the report level, users will still be able to see the underlying data table inside the report interface, but the option to export it as a file will be grayed out.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Using the Underlying Data Feature as a Report Viewer

Once the feature has been enabled by the report creator, accessing the data is incredibly straightforward. Here’s how you do it when viewing a published report.

1. Hover Over the Visual

Move your mouse over the chart you're interested in. The visual header with several icons will appear in the top-right corner.

2. Find the "More options" (...) Icon

Click on the icon with three dots (...). This will open up a context menu.

3. Choose How to View the Data

You will typically see two options for viewing the data. Understanding the difference is important:

• Show data point as a table: This option displays your visual in a different orientation. It essentially pivots your chart into a simple table of the aggregated data points. You'll switch from the graphical view to a matrix showing the same summary numbers that built the visual. This is useful for seeing all the numbers from the chart in one table.
• See records: This is the option that unveils the true underlying, row-level data. Clicking this opens a new view showing every single record contributing to the part of the visual you clicked on.

To get back to the report view, simply click "Back to report" in the top-left corner.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Next Level: Building a Custom Drill-Through Page

Viewing underlying data as a raw table is functional, but it's not always visually appealing or context-rich. The "next level" of providing this detail is by creating a dedicated drill-through page.

A drill-through page is a separate, hidden report page that you design to display detailed information about a single entity (like a customer, product, or region). It gives you full control over how the "underlying data" is presented.

Here’s a quick overview of how to set it up:

1. Create a New "Detail" Page: Add a new page to your report. This will be your drill-through landing page.
2. Add Your Detail Visuals: Populate this page with visuals that provide granular details. For example, if you want to drill through on a specific product, you might add a table of recent sales transactions for that product, KPI cards for its total profit, and a line chart of its sales trend over time.
3. Designate it as a Drill-Through Page: With the new page selected (and no visuals selected), go to the "Format your report page" pane. Find the "Page information" section and toggle "Allow use as a drill-through" to On.
4. Assign the Drill-Through Field: Go to the "Data" pane for the page. In the "Drill through" section at the bottom, drag the field you want to filter this page by into the well. For our example, you would drag the "Product Name" field here.

Now, go back to your main report page. When you right-click on a data point related to a product (e.g., a bar representing "Product A" in a sales chart), you'll see a new context menu option: "Drill through." Hovering over it will let you navigate to your new detail page, which will already be filtered to show data for only "Product A."

Final Thoughts

Mastering the ability to show and view underlying data in Power BI is a crucial step in moving from basic report creation to building dynamic analytical tools. It empowers everyone, from the creator to the end-user, to validate information, dig into details, and confidently answer questions on the fly.

While tools like Power BI are powerful, we believe accessing your data should be as simple as asking a question. With Graphed, we automate the entire reporting process by connecting directly to your sources like Google Analytics, Shopify, and Salesforce. Instead of building visuals and then drilling down through menus, you can just ask in plain language, "Show me a breakdown of sales in Canada last month," and get a detailed, interactive dashboard instantly. It gives you the power to explore underlying data without the learning curve.