Difference Between Power BI Import vs Direct Query
Power BI import is a mode of connecting to data sources and importing a copy of the dataset for internal processing within Power BI whereas the Direct Query mode helps you directly connect to the data source and query the underlying source. When you use Power BI import, a local copy of the data is stored internally within Power BI while in Direct Query, no data is imported into Power BI. Instead, queries are sent directly to the source database in real time. Import is suitable for smaller datasets that can fit into the available memory and Direct Query can be used for scenarios where you must build real-time data analytics as it always uses the current data.
Data Storage
- In Power BI import, data is imported into Power BI and stored in its internal data model. The data is loaded into the Power BI file (.pbix), and subsequent queries and calculations are performed on the imported data. It is suitable for smaller datasets that can fit into the available memory.
- With DirectQuery, no data is imported into Power BI. Instead, queries are sent directly to the source database in real-time. It is helpful for large datasets that might be impractical to import or for scenarios where you want the most up-to-date data without the need for regular refreshes.
Performance
- In Power BI import, given the data is loaded into Power BI, queries and visualizations can be faster since the data is already in memory. However, performance may degrade with huge datasets or complex transformations.
- In DirectQuery, performance is dependent on the speed and capacity of the source database. Since queries are executed in real-time, it allows for working with extensive datasets without the need for storing them in Power BI.
Data Refresh
- In Power BI import, data needs to be refreshed periodically to ensure that it reflects the latest changes from the source. It can be scheduled at regular intervals.
- In DirectQuery, since queries are executed directly against the source, the data is always up-to-date, providing real-time access to the latest information.
Data Transformations
- Using Power BI Import, data can be transformed and shaped within Power BI using Power Query Editor. This allows for cleaning, filtering, and aggregating data before it’s imported into the model.
- In DirectQuery, transformations are performed in the source database. Power BI only sends the query to the database, and the database engine handles the processing.
Data Source Support
- Power BI Import supports a wide range of data sources, including files, databases, online services, and more.
- DirectQuery supports specific data sources with DirectQuery capabilities, typically relational databases such as SQL Server, Oracle, and others.
Compatibility
- Power BI Import works well in scenarios where the data can fit into the available memory and where periodic data refreshes are acceptable.
- DirectQuery is suitable for scenarios where real-time access to large datasets is crucial, and the source database can handle the query load.
Table of contents
What is Power BI Import?
Power BI Import is a feature in Microsoft Power BI. This business analytics service provides interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their reports and dashboards. Power BI Import refers explicitly to the process of importing data into Power BI for analysis and visualization. When Power BI is connected to any data sources, a copy of the data is imported into Power BI.
Some of the critical processes associated with Power BI Import include:
Components | Description |
---|---|
Data Sources connectivity | Using the Power BI Desktop interface, you can connect with different data sources that include: • Flat file formats (Excel, CSV, PDFs, etc.) • Database (SQL Server database, Oracle, IBM, SAP, etc.) • Microsoft Fabric (dataflow, datamart, etc.) • Power platformsAzureOnline services (SharePoint, Dynamics, Salesforce, etc.) • Others (websites, Active Directory, etc.) You can choose one of the above-supported data sources to import data into Power BI for data analysis |
Transform Data | Post data import into Power BI, the Data Transformation feature can be used extensively to apply data cleaning and transformation to prepare the data for further processing. |
Data Modelling | Once the data is imported and transformed, you can create relationships between different tables, define calculated columns, and build measures using DAX (Data Analysis Expressions) language. |
Data Visualization | You can create interactive dashboards and reports using data visualization templates such as graphs, charts, maps, etc. to gain insights from your data. |
Data refresh | Power BI Import allows you to set up scheduled refreshes for your data, ensuring that your reports are always up-to-date with the latest information from your data sources. |
What is a Direct Query?
DirectQuery is a method of connecting to and querying data sources directly without importing the data into the Power BI model. In the DirectQuery method, Power BI sends queries directly to the underlying data source, and the results are displayed in the Power BI report or dashboard in real-time.
Some of the critical features and considerations of DirectQuery in Power BI includes:
Features | Description |
---|---|
Real-time Data Access | • DirectQuery allows you to access real-time or near-real-time data from your data source. • It is beneficial when dealing with large datasets that may be impractical to import into Power BI. |
Direct Connectivity to source data | • Unlike Import mode, where data is loaded into Power BI and stored in a separate model, DirectQuery avoids data duplication. • The data remains in the source system, and Power BI retrieves it dynamically as needed. |
Support to multiple data sources | • DirectQuery is supported for various data sources, including SQL Server, Azure SQL Database, Oracle, Teradata, and others. • The compatibility depends on the specific connectors and drivers available for the data source |
Performance Implications | • The performance of DirectQuery depends on the performance of the underlying data source and the efficiency of the queries generated by Power BI. • It’s essential to optimize your queries and ensure that your data source can handle the query load |
Limitations | • DirectQuery mode does not support all the features of Power BI Desktop. • Similarly, features such as quick insights in Power BI service are not supported in DIrectQuery for Semantic models. DirectQuery does not support automatic date/time hierarchy and drill-down features for the date column. • Switching from Import to DirectQuery mode is not allowed, though the opposite is possible. • There is a limit of 125 columns for results returning more than 500 records through DirectQuery mode if you are using a table or matrix visual. • If you are using a calculated column or calculated table that references a DirectQuery table, then the Power BI service will not support the Single Sign On (SSO) authentication mechanism. |
Performance and Load Considerations | • The refresh time of data visuals using DirectQuery mode for data connectivity is a key consideration for using DirectQuery. Any refresh time beyond 30 seconds can result in poor user experience and even page render error • Similarly, the number of users consuming the published Power BI report using DirectQuery mode can increase the load and hence impact the overall performance of the dashboard or reports. |
Security Considerations | • DirectQuery respects the security settings and permissions of the underlying data source. • Users in Power BI can only see the data they have permission to access in the data source |
Comparative Table
There are several similarities and differences between Power BI Import and DirectQuery. This section captures the critical differences between these modes in a comparative table below:
Category | Power BI Import | Direct Query |
---|---|---|
Data Sourcing | Power BI Import imports a copy of the data from the selected tables and columns into the Power BI Desktop | No data is imported and there is a direct connectivity to the data source. The tables and columns appear in Power BI for selection |
Data Storage | Data is loaded into the Power BI cache, and reports are based on the imported data | In DirectQuery, queries are sent to the data source in real-time, and Power BI does not store the data locally. |
Support to multiple data sources | Power BI Import supports a wide range of data sources | There are specific data sources that support Direct Query |
Performance considerations | Data rendering is faster compared to Direct Query as the imported data is stored internally in Power BI | DirectQuery performance depends on a variety of factors including the complexity of the query, data model, capacity, etc. |
Data Memory | Power BI Import is suitable for smaller datasets that can be loaded into memory. | DirectQuery is suitable for large datasets where loading into memory is not feasible. |
Data refresh | In Power BI Import, manual refresh or automatic refresh scheduling is required to reflect any changes to the underlying data set. | No data refresh is needed as it directly connects to the underlying dataset. |
Data Size | It supports the 1-GB semantic model definition. | No limitation to the data size. |
Advanced features | It supports advanced features such as Quick Insights, Calculated tables, Built-in Data hierarchy, clustering, etc. | No such features are available. |
Changes to data connectivity mode | Doesn’t support changing the mode from Direct Query to Power BI Import | Supports changing the mode from Power BI Import to Direct Query |
Data Visualization | Data visualization is based on the data query on the cached data in Power BI and hence the changes are immediately visible | Data visualization is based on the data source as Power BI sends queries to the data source and hence the changes may take some time to load. |
Similarities
Despite of differences between Power BI Import, and DirectQuery, there are some similarities between these modes that can help you choose the right mode for your data visualization requirements.
Some of the critical similarities are highlighted below:
Data Transformation and Modeling
- Both Import and DirectQuery allow you to perform data transformation and modeling using Power BI’s Power Query Editor.
- You can apply various transformations, clean data, and create relationships between tables in both Import and DirectQuery modes.
Report Creation and Visualization
- Once the data is loaded into Power BI, whether through Import or DirectQuery, you can create reports, dashboards, and visualizations similarly.
- Users can leverage the same set of visualization tools and features regardless of the data connection type.
Data Exploration
- Data exploration capabilities are available in both Import and DirectQuery.
- Users can explore the data, drill down into details, and analyze information interactively.
Query Editor
- Power Query Editor is used in both Import and DirectQuery modes to shape and transform data before it is loaded into the Power BI model.
DAX Formulas
- Both Import and DirectQuery modes support Data Analysis Expressions (DAX) formulas for creating calculated columns, measures, and other calculated elements within the Power BI model.
Data Refresh
- Both Import and DirectQuery support data refresh capabilities, allowing you to keep your Power BI reports up-to-date with the latest data from the source.
In summary, the choice between Import and DirectQuery depends on factors such as data size, performance requirements, data freshness needs, and the capabilities of the source system. Import is suitable for smaller datasets and scenarios where periodic refreshes are acceptable, while DirectQuery is suitable for larger datasets and scenarios requiring real-time access to the latest data.
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