Power BI Import vs. Direct Query: Which ModeYou Should Use?

Power BI Import vs Direct Query

One of the most critical choices when using Power BI is connecting to your data sources using direct query or import modes. This decision can significantly influence overall functionality, performance, and data freshness. 

While import mode allows you to input data into Power BI for quick analysis, direct query provides instantaneous access to data. Selecting the appropriate mode for your project requires understanding its advantages and disadvantages. Let’s examine the main distinctions between Power BI import vs. direct query and the situations in which each method works well.

Understanding Power BI Import

In this method, the data is imported and stored in a compressed in-memory column of Power BI. It is the perfect method for dealing with a small dataset or one that isn’t updated frequently. Users may do complex computations, build advanced data models, and generate reports and visualizations depending on input data using the language of DAX or the data analysis expressions.

Understanding Power BI Direct Query


Your semantic model will query the data source directly at runtime when you choose the direct query method of connection. A fresh query is started whenever an interaction or filter is used with the report. No data is stored here; whenever you want to query the data, you will use the one present at the data source. 

Power BI Import – When to Use It?

Import is excellent when creating calculated measures and columns, performing extensive data transformations, or building complex relationships. It offers the flexibility to shape and enrich the data per specific requirements. Besides, as mentioned before, it is perfect for small datasets that can be easily compressed in the memory. It also offers fast query response time and user experience.

Advantages of Power BI Import

Listed below are the advantages of Power BI – Import:

  • Since the data is loaded in the system, it gives better performance needed for visualization.
  • It also enables faster report generation, especially when the datasets are large.
  • Data manipulation is more accessible as the users have complete control over it.
  • Users do not have to rely on pre-built external systems, such as server analysis services and SQL, to create custom calculations and logic for business needs.
  • Users can have offline access to reports generated by Power BI desktop and online services, like OneDrive or Sharepoint.
  • Users won’t need an internet connection as the data is already in the system.

Limitation with Power BI Import

Let’s look at the limitations of working with Import:

  • There is a limit to the data volume that can be worked on using this method. Hence, it may not be the best option for companies analyzing massive amounts of data.
  • It may not support all kinds of data structures and formats. Thus, it can create a problem, especially when integrating from multiple sources.
  • It requires manual data refreshing.
  • You may face issues when you are dealing with complex datasets.

How is Power BI Import Used?

When using Import in Power BI, data is loaded from sources such as CSV files, Excel, and cloud-based services like Azure, Salesforce, Microsoft Dynamics, and databases. This method exports the data from these sources and imports it to Power BI.

Power BI Direct Query – When to Use It?

The direct query is best for the below-mentioned scenarios:

  • When the data changes frequently, and you need real-time insight or reporting.
  • You are required to handle large datasets without pre-aggregating.
  • The underlying source defines security rules.
  • When there are data sovereignty restrictions.
  • The source contains multidimensional sources, such as SAP BW.

Advantages of Power BI Direct Query

Here are some benefits of using direct query:

  • You get the most up-to-date data as it is queried from the source.  
  • The report is refreshed every 15 minutes or when there is a change in filters or interactions, ensuring the data remains fresh.
  • This results in significantly smaller and more manageable Power BI desktop files because no data caching is involved.
  • Since there is no cache, you would not need much storage to use direct query.

Limitations with Power BI Direct Query

There are certain limitations when working with the direct query:


  • Since the data is refreshed every 15 minutes, creating and knowing the timelines of the data becomes the cause of concern.
  • The file sizes are reduced since you no longer work with caches.
  • Your system will not have enough storage space.

How is Power BI Direct Query Used?

DAX is used to get data using this method. Following receipt of the report’s DAX query, the semantic model creates a new set of queries executed on your data source to obtain the necessary data. Power BI will make SQL queries to get the data it needs, for instance, if your data source is a SQL Server database. Various data sources may generate queries in different query languages.

Key Differences Between Power BI Import and Direct Query

In the Import method, a copy of the data is obtained from the chosen tables and columns. Power BI Desktop uses the loaded data as you design or work with visuals. You need to import the entire semantic model once more to refresh the data and observe any changes to the underlying data from the first import or the most recent refresh.


In the direct query method, no data is imported. You may choose which tables and columns to include in the Power BI desktop fields list for relational sources. The selected cube’s dimensions and measurements appear in the Fields list for multidimensional sources. When you create or work with visuals, the Power BI desktop searches the underlying data source to ensure you always deal with the most recent data version.

Let’s look at Power BI import vs direct query key differences based on different features:

FeaturesPower BI ImportPower BI Direct Query
Size1GB per datasetNo limitations
Target audienceSmall and medium datasetsDatasets greater than 1GB
Data support sourceImport from multiple sourcesCan be imported from only one source
SecurityYou may enable row-level security on import only for the PBI dataset.Reuse on-premises row-level security in analysis services tabular by using DAX expressions.
PerformanceHigh-performing query engineSince the queries are processed in real-time, dependency is on the network and information sources. 
Change data connectivity modeCannot change from import to data queryYou can switch from direct query to import
Change of data in underlying dataYou will have to refresh the report manually and republish or reschedule it.Power BI caches the data for faster performance. Hence, a refresh is required for the update.
Q&AAvailableOnly in preview
Power BI data storageIt is stored in the Power BI serviceIt does not store any data
Quick insightsAvailableNot available
Schedule RefreshMaximum eight schedules in a dayEvery 15 minutes
Calculated tablesAvailableNot supported
Power BI gatewayOnly the most recent data is neededThe on-premise data source is required
ClusteringAvailableNot available
Transformations of dataSupports all kindIt supports many with some limitations
DAX expressionsSupport all DAX functionsComplex functions like time intelligence are restricted. It is supported if the underlying source has a data table.
Modeling of dataNo limitationsCertain limitations, including relational connections and auto-detect tables, only apply in one way.
In-built hierarchyAvailableNot available

Scenarios Favoring Power BI Import and Data Query Modes

Let us look at different scenarios and determine which mode will be the best. These are some common scenarios that often arise in day-to-day work. Knowing which mode will help the best will be valuable in deciding the perfect Power BI mode for your company.

Data transformation and explorationImportIt is best to clean, shape, and transform the data before use. Power BI enables computation, combining data from several sources and building a single model. When working with several data sources that need to be harmonized, this is really helpful.
Real-time data analysisDirect queryIt is great when you need minute-to-minute analysis. It is excellent for monitoring website data, stock price monitoring, and analyzing sensor data.
Offline accessibilityImportSince data is already imported and stored, it offers offline accessibility. You can do anything, like create, modify, and even view reports without any internet connection.
Evolving and large datasetsDirect queryImporting data can be challenging when large datasets are involved. Therefore, data query is best as it gives you current and refreshed data without any limitations.
Complex calculationsImportYou can carry out intricate computations, aggregations, and modeling thanks to import mode. This is useful for creating custom measurements, complex KPIs, and calculated columns that depend on data from several sources.
Data source consistencyData queryIf you are working on situations where data source consistency is a must, like compliance monitoring or financial reporting, data query is the best option.  It helps prevent data staleness and inconsistencies by ensuring that your results accurately represent the original data.
Performance optimizationImportPerformance can be easily optimized by importing data in Power BI. Moreover, since the data is already in the system, queries and visualizations respond faster.  Hence, it offers a smooth user experience even when working on large datasets.
Data compliance and securityImport The data is stored in the system, so there is better control of it. This makes it more compliant and secure than data query. Therefore, it is excellent for companies bound by regulatory compliance and strict regulations.
Resource efficiencyData querySince the data is not stored internally, it is more resource-efficient. It is great for situations when there is a memory or storage concern. It is mostly with large companies where there are IT resource limitations.


The choice between Power BI’s import and direct query modes ultimately comes down to your particular use case, amount of data, and analytical needs. The direct query is preferable for extensive, regularly updated data that has to be analyzed in real-time, although import mode is best for smaller datasets with quick response times. You may select the optimal mode for your purposes and provide a comprehensive solution that meets your data performance and freshness criteria by being aware of each technique’s advantages and disadvantages. 

Remember that you may constantly adjust and switch modes as your company needs change. If you want to know more about Power BI, its uses, and which one to learn, check out the articles and Power BI certifications at CCSLA. You can easily be an expert in this field without spending much time by completing bootcamp programs, such as the Data Science & Engineering bootcamp from CCSLA which gets you job-ready in just 12 weeks.