How to Tell if Direct Query or Import in Power BI

Choosing between DirectQuery and Import mode in Power BI is one of the most fundamental decisions you'll make when building a report, directly impacting performance, data freshness, and functionality. Once a report is built, however, figuring out which mode it uses can sometimes feel like a bit of a detective mission. This article will show you the simple ways to identify a report’s data connection mode in both Power BI Desktop and the Power BI Service.

First, What Are Power BI Query Modes?

Before checking which mode a report uses, it's helpful to understand the basic differences between the main options. Power BI connects to data sources using one of three primary storage modes: Import, DirectQuery, or a hybrid known as Composite/Dual mode.

Import Mode

This is the most common and often highest-performing mode. When you use Import mode, Power BI pulls a full copy of the data from your source (like an Excel file, a SQL database, or a SaaS application) and stores it within the Power BI file itself (the .PBIX file). This data is compressed and optimized by Power BI's internal VertiPaq engine, which is the "secret sauce" that makes reports so fast.

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DirectQuery Mode

As the name suggests, DirectQuery mode connects directly to the data source. No data is actually copied into the Power BI file. Instead, every time you interact with a visual — clicking a slicer, filtering a chart, or even just opening the report — Power BI sends a live query to the underlying source to fetch the latest data.

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Composite (or Mixed) Mode

Composite models allow you to use a mix of both Import and DirectQuery within the same report. For example, you could import a small 'Date' dimension table for fast slicing but use DirectQuery for a massive 'Sales' fact table that needs to be up-to-the-minute. Tables can also have a 'Dual' storage mode, which allows Power BI to decide whether to query the imported cache or the live source depending on the context of the query.

Why It Matters Which Mode You're Using

Understanding a report's storage mode is central to managing user expectations and troubleshooting issues. If a user complains that a report is slow, a good first question is, "Is it using DirectQuery?" If they ask why the sales data is from yesterday, "Is it an Import model that missed its refresh?" The mode dictates a report's fundamental behavior and limitations.

• Performance Issues: Users expect snappy, responsive reports. A report built in DirectQuery on a slow SQL server will never feel as fast as a well-designed Import model. Knowing the mode helps you set realistic performance expectations.
• Data Freshness Questions: In many business scenarios, data that is refreshed once a day is perfectly fine (e.g., daily marketing summaries). For others, like tracking live website traffic or monitoring a production line, real-time data from a DirectQuery connection is a requirement.
• Maintenance and Governance: Import models require you to manage data refresh schedules and gateways. DirectQuery models require you to manage the security and performance of the underlying data source. The overhead is quite different.

How to Check the Query Mode in Power BI Desktop

If you have access to the original .PBIX file, identifying the query mode is straightforward. Here are three simple methods, starting with the easiest.

Method 1: The Status Bar (The Quickest Way)

This is the fastest high-level check. Simply open your .PBIX file in Power BI Desktop and look at the bottom-right corner of the window.

You’ll see text stating the Storage Mode:

• No text: If there's no mention of a storage mode, your report is 100% in Import mode.
• Storage Mode: DirectQuery: This means all tables in your model are using a DirectQuery connection.
• Storage Mode: Mixed: This indicates you have a Composite model, with some tables set to Import, some to DirectQuery, and potentially some set to Dual.

This little corner displays the overall status of your report at a glance and is a great first stop.

Method 2: The Model View

For a detailed, table-by-table view of storage modes (especially useful in Composite models), the Model View is your best tool.

1. On the left-hand navigation pane, click on the Model view icon (it looks like three connected boxes).
2. Select a table in your data model canvas.
3. If the Properties pane isn't already visible on the right, go to the "View" ribbon and check the box for "Properties."
4. With a table selected, scroll down in the Properties pane until you find the Advanced section.
5. Here, you'll see a drop-down menu for Storage mode. It will clearly state whether that specific table is set to Import, DirectQuery, or Dual.

You can also just hover your mouse over a table header in the Model view canvas, and a tooltip will appear with details about the table, including its storage mode. This method is incredibly helpful for diagnosing which specific tables in a mixed model might be contributing to performance issues.

Method 3: The Performance Analyzer

Another helpful method that gives you indirect clues is the Performance Analyzer. This tool is primarily used for optimizing visuals, but its output reveals the type of queries being run.

1. Go to the View ribbon and click Performance analyzer.
2. The pane will open on the right. Click Start recording.
3. Now, interact with your report visuals. Click on a slicer or cross-filter a chart.
4. As each visual refreshes, the Performance Analyzer will log the actions. Expand a visual's entry and you will see components like "DAX query," "Visual display," and others.
5. If you see an entry named "Direct query" for a visual, that's a dead giveaway. Its duration is the time Power BI spent waiting for the source system to return data. In an Import model, you'll only see entries like "DAX query," which indicates the query was run against the internal VertiPaq engine.

How to Tell in the Power BI Service

What if you don't have the .PBIX desktop file and can only view the published report online in the Power BI Service? This is a common scenario for many business users. While there isn't a direct label like in Desktop, you can still find strong clues.

Check the Dataset Settings

The most reliable way is to look at the dataset connected to the report.

1. Navigate to the workspace where the report is published.
2. Find the dataset that powers your report (it usually has the same name and a different icon).
3. Hover over the dataset and click the three-dot menu (...) and select Settings.
4. Now, look for two key sections:

"Feel" the Report Performance

This is less scientific but often shockingly accurate. How does the report feel to use?

• If you open the report and all the visuals load almost instantaneously, and filtering slicers gives you immediate feedback, you're almost certainly using an Import model. The optimized data is waiting in memory, ready to go.
• If you open the report and have to wait several seconds for visuals to render, or if every time you apply a simple filter you see spinners on the charts, you are likely looking at a DirectQuery report. That "thinking time" is the delay while Power BI sends a query to the source and waits for a response.

Final Thoughts

Knowing how to spot the difference between DirectQuery and Import will help you better understand, manage, and troubleshoot your Power BI reports. In Power BI Desktop, your best friend is the status bar for a quick confirmation or the Model view for detailed, table-specific information. In the Power BI Service, clues in the dataset settings and the report’s general responsiveness can quickly point you in the right direction.

At the end of the day, managing storage modes, data gateways, and refresh schedules is part of the overhead that comes with powerful reporting tools. At our company, we built Graphed to simplify this entire process. Instead of deciding between import caches and direct connections, you connect your data sources in seconds, and our AI-powered platform handles the rest. You get real-time dashboards by simply describing what you want to see in plain English, allowing you to focus on insights, not on the technical setup behind them.