"Decoding Connection Modes: Maximizing Insights with Import, DirectQuery, and Composite Models

"Decoding Connection Modes: Maximizing Insights with Import, DirectQuery, and Composite Models

It's important to note that while there might not be explicit row limits for DirectQuery or Import modes, the overall performance and usability of reports can be impacted by the size and complexity of the dataset, the available system resources, and the performance characteristics of the underlying data sources. Striking a balance between dataset size, data modeling, and report performance is crucial when working with large datasets in Power BI.


    - Import mode allows you to load data into Power BI's internal VertiPaq engine, storing the data in-memory within the PBIX file.

   - The maximum size of a Power BI Desktop (.pbix) file is 1 GB.

   - There isn't a strict row limit in the import mode, but the performance of Power BI reports might degrade if the dataset size becomes too large.

   - Large datasets may lead to increased file sizes, which can impact performance and usability.



1.  Performance:  Imported data is stored locally, offering faster query performance and responsiveness.

2.  Disconnected Environment:  Data is cached within the Power BI file, allowing offline access and independence from the original data source.

3.  Data Transformation:  Enables extensive data modeling, transformation, and custom calculations within Power BI.



1.  Data Freshness:  Requires manual refresh to update data, potentially leading to outdated information in reports.

2.  Storage Limitations:  Limited by the available storage space in the Power BI file. Large datasets can significantly increase file sizes.



1.  Real-Time Data:  Not suitable for real-time or frequently changing data scenarios.

2.  Large Data Volumes:  May face limitations with large datasets due to storage constraints.



   - DirectQuery mode connects directly to the data source, so there isn't a row limit imposed by Power BI.

   - However, the performance of DirectQuery can be affected by the limitations and performance capabilities of the data source.

   - Large datasets or complex queries might lead to slower performance and longer query times.



1.  Real-Time Data Access:  Connects directly to the data source, providing real-time access to the most recent data.

2.  Scalability:  No limitations on data volume as it doesn't store data locally.

3.  No Data Duplication:  Ensures users are always viewing the most up-to-date information from the source system.



1.  Performance Overhead:  Query performance can be affected as queries are executed directly against the source system.

2.  Complexity in Modeling:  Limited modeling and transformations compared to Import mode due to query constraints.



1.  Data Source Support:  Not all data sources are supported for DirectQuery, and some may have limitations on supported functionalities.

2.  Security Constraints:  Security and access control settings of the data source affect what can be queried.


Composite Models (Dual):

    - Composite models allow a combination of both Import and DirectQuery modes within the same report.

   - Similar to Import, there isn't a strict row limit for the Import part of the model, but file size limitations still apply.

   - The DirectQuery part's performance depends on the connected data source's capabilities and restrictions.



1.  Flexibility:  Provides the flexibility to use both Import and DirectQuery modes within the same report, combining their advantages.

2.  Performance and Real-Time Access:  Utilizes Import for aggregated data and DirectQuery for detailed or real-time data.



1.  Complexity:  Managing both modes in a single report can increase complexity in data modeling and maintenance.

2.  Resource Consumption:  Consumes more resources due to the dual usage of Import and DirectQuery.



1.  Data Source Compatibility:  Similar limitations to DirectQuery mode apply based on the data source's compatibility and restrictions.


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Power Platform , D365 CE & Cloud
Power Platform , D365 CE & Cloud

Dynamics 365 CE, Power Apps, Powerapps, Azure, Dataverse, D365,Power Platforms (Power Apps, Power Automate, Virtual Agent and AI Builder), Book Review

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