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What is Import Mode in Power BI?

Cody Schneider•

When you're working with Power BI, one of the first and most critical decisions you'll make is how to connect to your data. Power BI offers different data connectivity modes, and the default - and often best - choice is Import Mode. This article breaks down exactly what Import Mode is, how it works, its major benefits, its limitations, and when you should use it over other options.

What is Power BI Import Mode?

Import Mode is Power BI's default method for connecting to data sources. When you use Import Mode, Power BI copies a snapshot of your data from the source systems (like an SQL database, an Excel file, or a SaaS application) and loads it directly into the Power BI file (.PBIX). This data is then stored and compressed inside a high-performance, in-memory engine called the VertiPaq Analysis Services engine.

Think of it like this: instead of going back to the original library every time you need to look something up, you’re making a photocopy of the most important chapters and keeping them on your desk for instant access. Once the data is imported, all your interactions within the Power BI report - slicing data, changing filters, running complex calculations - query this internal, cached copy. The connection to the original source is only used when you decide to refresh the data, pulling in a new, updated snapshot.

This in-memory approach is the secret behind Power BI's incredible speed and flexibility, allowing you to build rich, interactive reports that respond instantly to user input.

How Import Mode Works: A Step-by-Step Look

Understanding the workflow of Import Mode helps clarify why it’s so powerful. Here is the typical process from connection to report.

Step 1: Connecting to a Data Source

Your journey begins in the Power BI Desktop application, where you select "Get Data." You'll choose from hundreds of available connectors, whether you're pulling from a simple Excel workbook, a cloud-based Salesforce account, or an on-premise SQL Server database. Power BI will then ask for your credentials to establish a connection.

Step 2: Selecting and Transforming Data in Power Query

Once connected, you don’t have to import everything. The Power Query Editor opens, which is your workshop for preparing the data. Here, you can:

  • Choose the specific tables and columns you need for your report.

  • Filter out unnecessary rows (e.g., only importing sales data from the last two years).

  • Clean up messy data, such as correcting typos or splitting columns.

  • Merge data from different sources into a single, unified table.

This step is crucial for performance. By only importing the data you absolutely need, you create a smaller, more efficient model.

Step 3: Loading Data Into the VertiPaq Engine

When you click "Close & Apply" in the Power Query Editor, the magic happens. Power BI executes the query steps you defined, pulls the transformed data from the source, and loads it into its internal VertiPaq engine. The engine uses a columnar database structure and advanced compression algorithms to store the data efficiently, significantly reducing the file size and boosting query performance. At this point, the data physically resides within your .PBIX file.

Step 4: Building Reports and Writing DAX

Now that the data is in memory, you can start building your report. As you drag and drop fields onto visuals or create powerful analytical calculations using Data Analysis Expressions (DAX), Power BI is querying the hyper-fast VertiPaq engine, not your original source. This is why visuals render almost instantaneously, even with millions of rows of data.

Step 5: Publishing and Scheduling Refreshes

After creating your report in Power BI Desktop, you publish it to the Power BI Service (the cloud-based component). The dataset, which contains your imported data, is published along with the report. Since the data inside is a snapshot from when you last hit "Refresh," you'll need to set up a scheduled refresh. In the Power BI Service, you can schedule the dataset to refresh automatically - for example, every morning at 6 AM - to pull the latest data from the source systems.

The Pros: Why You Should Love Import Mode

Import Mode is the default for a reason. It comes with several advantages that make it the best choice for the majority of reporting scenarios.

Amazing Speed and Performance

Because all data lives inside Power BI's highly optimized in-memory engine, queries are incredibly fast. Users don't have to wait for a slow database to return results. Reports feel snappy and responsive, which is essential for encouraging data exploration and adoption by users.

Full Power Query and DAX Support

Import Mode gives you a limitless playground. You can use every single transformation available in the Power Query Editor and write any DAX measure you can dream up without restrictions. Other connection modes, like DirectQuery, have limitations on the types of functions you can use.

Freedom to Combine Multiple Data Sources

This is a huge benefit. You can easily pull data from a Google Analytics report, add sales figures from a SQL database, and layer on budget information from a Google Sheet. Import Mode allows you to merge all these disparate sources into one cohesive data model within Power BI.

Reduces Load on Source System

Once the data is imported, your report users are not hammering the source database with constant queries every time they click a slicer. The source system is only accessed during the scheduled refresh, which can be configured to run during off-peak hours. This prevents your analytical reporting from slowing down day-to-day operations.

Enables Offline Development

Because the data is stored in the .PBIX file itself, you can work on your Power BI report from anywhere, even on a plane without internet access. You will still be able to create measures, design visuals, and interact with the data you last imported.

The Cons: When Import Mode Isn't the Right Choice

Despite its many strengths, Import Mode is not a perfect solution for every situation. Here are its primary limitations.

Data Size and Memory Limits

The biggest challenge is dataset size. The data you import must fit into memory. With a Power BI Pro license, your published dataset is limited to 1 GB. While Premium capacity allows for much larger datasets, you're still constrained by available system resources. For datasets in the hundreds of gigabytes or terabytes, Import Mode is not feasible.

Data Is Not Real-Time

The data in your report is only as fresh as your last refresh. With a Pro license, you're limited to 8 scheduled refreshes per day. While Premium offers up to 48 refreshes, this still isn't real-time. If you need a dashboard that shows what is happening this very second (e.g., in a manufacturing or stock trading scenario), Import Mode is not the answer.

Potentially Long Refresh Times

For large datasets, the refresh process itself can take a significant amount of time and consume substantial resources in the Power BI Service, potentially impacting performance for other users during the refresh period. Techniques like incremental refresh can help, but it's still a consideration.

Import Mode vs. Other Connectivity Modes

To fully appreciate Import Mode, it helps to compare it to the alternatives: DirectQuery and Live Connection.

  • Import Mode: Copies data into Power BI. It's fast, flexible, but not real-time and has size limits.

  • DirectQuery: Leaves the data in the source system. Power BI sends queries back to the source for every visual. This is great for massive datasets and near real-time needs, but performance depends entirely on the source database, and it has significant DAX limitations.

  • Live Connection: A special version of DirectQuery that connects to an underlying "semantic model" like Azure Analysis Services or a previously published Power BI dataset. You can't transform the data or modify the model, you are purely a report builder on top of a curated model.

In short, Import Mode should be your default choice unless you hit a significant limitation related to data size or the need for real-time reporting.

Tips for Optimizing Import Mode Reports

If you choose Import Mode, here are a few best practices to ensure your report performs at its best:

  • Import Only What You Need: Never just select a whole table and import it. In Power Query, remove any columns and filter any rows that you don't need for your report. A leaner model is always a faster model.

  • Mind Your Data Types: Ensure columns are set to the proper data type (e.g., format numerical IDs as "Whole Number" instead of "Text"). This helps the VertiPaq engine with compression and performance.

  • Build a Star Schema: Organize your data into fact tables (like sales transactions) and dimension tables (like products, customers, and dates). This classic data modeling structure is the most efficient for Power BI.

  • Leverage Incremental Refresh: For very large, growing datasets, configure incremental refresh in the Power BI Service. This allows Power BI to only refresh new and updated data, making the refresh process dramatically faster.

Final Thoughts

Power BI's Import Mode is the workhorse of BI reporting dashboards. It offers the best performance, the most flexibility, and the richest feature set by bringing a compressed copy of your data into its high-speed in-memory engine. While it has limitations related to data size and freshness, it's the ideal choice for the vast majority of business analytics scenarios.

Of course, managing data connectors, optimizing queries, and configuring refresh schedules in traditional BI tools can still feel like a full-time job. At Graphed, we focus on removing that complexity entirely. By connecting your tools like Google Analytics, Shopify, and Salesforce directly to our platform, you skip the learning curve. We handle all the connections and data syncing automatically. You can just ask questions in plain English like, "show me a dashboard of ad spend vs. revenue by campaign," and watch as a live, interactive dashboard gets built for you in seconds, not hours.