Data drives today’s digital-driven businesses and is considered an asset to strengthening a data-driven decision-making process. Microsoft’s Power BI, a powerful business analytics tool, offers a platform to collect, analyze, and visualize data through attractive visualization and interactive reports, empowering businesses to boost profitability and uncover insights.
When you connect to data in Power BI, there are two primary modes: Import and DirectQuery. Power BI Import is constantly compared to Direct Query.
The Import method captures a data snapshot and caches it in the Power BI Desktop, whereas the Direct Query method executes queries directly to the source at runtime.
The one you choose depends on several factors, such as the amount of data to be handled, the frequency of updates, organizational goals, etc. Based on these factors, a decision can be made.
Before we investigate the difference between Power BI Direct Queryand Import, let’s individually review their features, pros, and cons.
What is Power BI Import?
Import mode is the most common mode used to develop datasets. Thanks to in-memory querying, this mode delivers fast performance. It also offers modelers design flexibility and support for specific Power BI service features (Q&A, Quick Insights, etc.). Because of these strengths, it’s the default mode when creating a new Power BI Desktop solution.
Data from disparate sources can be imported into a Power BI data file with a PBIX extension using Power BI Import. The file executes in memory and is optimized by the ‘VertiPaq’ engine, which creates responsive reports and dashboards.
Once data is imported into the file and the model is created, the file is uploaded to the Power BI service to make reports and dashboards.
The import mode of data storage empowers users to easily import data into Power BI Desktop by merely navigating to the data source, choosing the tables to be added, and clicking Import.
It is recommended when the data size is less than 1 GB and the data has little change. All the data interactions and filters will be applied to the compressed source rather than the main one.
With Power BI Import, users can design complicated data models and perform advanced calculations using the Data Analysis Expressions (DAX) language to create data visualizations. Data is loaded from different sources, such as CSV files, Excel files, databases, and cloud-driven services, onto Power BI for further analysis.
What is Direct Query in Power BI
DirectQuery mode is an alternative to Import mode. Models developed in DirectQuery mode don’t import data. Instead, they consist only of metadata defining the model structure. When the model is queried, native queries retrieve data from the underlying source.
Power BI Direct Query is a powerful deployment method that extracts data from different sources when reports are executed to make the output live. It directly connects to the data source and maintains that connectivity while executing reports. It reflects changes in real time, so a refresh is not needed manually. It is recommended when data is updated frequently or when the volume of data is significant.
Power BI sends queries to the data source to create visual effects. The dashboard will query the data source at runtime and fetch the real-time results. All interaction with reports will result in a new query that will be directly executed.
Since no data is imported in Power BI, the queried data is available in the data source itself. Each query is limited to returning less than or equal to 1 million rows. With Power BI Direct Query, users can build data models that span multiple data sources and tables to generate real-time analytics of the data.
Power BI Import vs. Direct Query: Pros and Cons
Pros of Power BI Import:
Enhanced, responsive, and faster performance
Data import without size limitation
Supports all DAX functions
It avoids throttling because of network delay
Seamless data integration by caching data from multiple sources
Advanced modeling and transformation
Greater functionality
Cons of Power BI Import:
Limited scalability and flexibility
It is not possible to change data connectivity
Data size limits
Pros of Direct Query:
Always showcases current and real-time data
Offers importing data from multiple sources
Schedule Refresh every 15 minutes
Visualizations from huge datasets
Smaller and simpler Power BI files
No duplication of data
Enhanced scalability
Cons of Direct Query:
Slow processing because of dependency on network
No offline access
Limited transformations
Power BI Import vs Direct Query: Comparing Two Modes for Data Connection
Parameters
Power BI Import
Power BI DirectQuery
Performance
It has a high-performance query engine, and the data model is already cached with no latency, but with more volume, it may degrade.
Since queries are processed in real-time, network connectivity is crucial. If indexes are well created, they perform well.
DAX Expressions and Transformations
Supports all DAX functions and advanced Power Query transformations for shaping the data before importing it
Restricted support for DAX functions and transformations since you can use limited data available in the data source
Schedule Refresh
Hourly/daily programmed async jobs with a maximum of eight schedules per day
Schedule at every 15-minute interval or in real-time
Size
Approximately 1GB per dataset/model
No limit to storing data in an on-premises database
Source of Data
Importing data from multiple sources
Importing data from a single source
Data Modeling
No limitations
Some limitations
In-built Hierarchy
Accessible
Not accessible
Data Storage
Data is preserved in the Power BI Service since it is in the cloud
The cloud service will not store any data; it will be stored locally
Data Availability
If data refresh doesn’t work, the last data available in the model is used
If data refresh doesn’t work, the report goes black since data is not stored
Change in Data Connectivity Mode
Cannot change from Import to Direct Query
The mode can be changed from Direct Query to Import
Target Groups
Small to Medium Datasets
Large Datasets (greater than 1 GB)
Security
Users can create row-level security on the PBI dataset
Users can reuse on-premises row-level security for Analysis Services
Clustering, Quick Insights, Calculated Tables
Available
Not available
Flexibility and Control
There is more control over data; hence, creating complex data models is more accessible but may not be suitable for larger datasets.
Since data is not stored in Power BI, it is not that flexible in creating complex data models, but it can easily manage large datasets.
Direct Query vs Import: When To Use What?
Whenever there is a comparison between Direct Query and Import Power BI, there are situations when one of them is recommended over the other. Here are specific suggestions:
Power BI Direct Query is suggested when:
There is a large amount of data that is frequently updated
You need to access real-time data or near real-time data
There is a need to leverage the power of the data source
Power BI Import is suggested when:
Data is less than 1 GB and not continuously updated
The data set is relatively more minor and more responsive
You need to perform complicated transformations
You need to create a data model with multiple data sources
There is a need to work offline or share reports with others
Power BI Import vs Direct Query: The Wrap-Up
As we compare Direct vs Import Query in Power BI, we see that both modes of connecting data can be combined if needed. They can be combined in the same report, taking advantage of both features.
This can happen using the Dual Storage mode, wherein some tables are imported while some are directly referred to. This gives you a dual advantage of faster speed of Import with Power BI Import and real-time access to data with Power BI DirectQuery.
The ongoing debate on Power BI Import vs. DirectQuery is a long one. The above analysis can be of great help as you analyze it. Both have their own set of characteristics to display as the situation arises.
Finally, the conclusion depends on the organizational requirements and availability of skilled resources.
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