Best Practice for Import vs. DirectQuery Mode in Power BI Reports with Dimensional and Fact Tables

[HamidBee]

Hello Community,

I'm delving into Power BI reporting and came across a scenario in a tutorial (applicable to Azure Synapse but relevant to Power BI in general) where DirectQuery mode was used for all tables in a data model, including both dimensional and fact tables. This raised a question in my mind about the optimal approach when dealing with different types of tables in Power BI reports.

Wouldn't it make more sense to use Import mode for dimensional tables and reserve DirectQuery mode only for the fact tables? I'm thinking this could potentially optimize the performance and efficiency of the reports, especially considering the typically smaller size of dimensional tables and the larger volume of data in fact tables.

I'd appreciate any insights or experiences on this matter. Is there a general best practice in such scenarios, or does it depend heavily on the specific context of the data and the reporting needs?

https://microsoftlearning.github.io/DP-500-Azure-Data-Analyst/Instructions/labs/04-create-a-star-sch...

Thank you for your guidance!

[fabricator1]

Here is some information on that topic: 
Use composite models in Power BI Desktop - Power BI | Microsoft Learn
User-defined aggregations - Power BI | Microsoft Learn 
Use storage mode in Power BI Desktop - Power BI | Microsoft Learn

Here are some labs:
https://microsoftlearning.github.io/DP-500-Azure-Data-Analyst/Instructions/labs/08-create-a-composit...

https://microsoftlearning.github.io/DP-500-Azure-Data-Analyst/Instructions/labs/10-improve-performan...
https://microsoftlearning.github.io/DP-500-Azure-Data-Analyst/Instructions/labs/11-improve-query-per... 

https://microsoftlearning.github.io/DP-500-Azure-Data-Analyst/Instructions/labs/12-improve-query-per...

From my own experience I have almost always used only Import mode

[Anonymous]

Hi @HamidBee 
We haven’t heard from you on the last response and was just checking back to see if your query got resolved. Otherwise, will respond back with the more details and we will try to help.
Thanks

[HamidBee]

Hi. I'm just waiting for an answer to my question. Thanks.

[Anonymous · Accepted solution]

Hi @HamidBee 

You are right. Whether to import or use DirectQuery for a table depends on several factors, and your intuition about using Import for dimensions and DirectQuery for facts is often a good starting point.

Here's a breakdown of the pros and cons of each approach for different table types:

Dimensional Tables:

Import:

• Pros:
  • Faster performance: Queries against smaller dimensional tables are faster when the data is stored locally within the Power BI model.
  • More flexibility: You can perform complex transformations and calculations on imported dimensions in Power Query and DAX.
  • Offline accessibility: Reports remain accessible even if the data source is unavailable.
• Cons:
  • Larger model size: Increases file size and potentially impacts sharing and cloud storage costs.
  • Stale data: Requires scheduled refreshes to reflect updates in the source data.

DirectQuery:

• Pros:
  • Real-time data: Displays the latest data as soon as it's available in the source, ideal for frequently changing dimensions.
  • Smaller model size: Reduces file size, especially beneficial for large datasets.
• Cons:
  • Slower performance: Queries can be slower depending on the data source and network latency.
  • Limited data manipulation: Fewer transformations and calculations are possible compared to imported data.
  • Source dependency: Relies on continuous availability of the data source.

Fact Tables:

Import:

• Pros:
  • Offline accessibility: Enables report usage even when the data source is unavailable.
  • Aggregation optimization: Allows pre-aggregation of data for faster performance on complex queries.
• Cons:
  • Large model size: Can significantly increase file size, impacting performance and storage costs.
  • Stale data: Requires scheduled refreshes to reflect updates in the source data.

DirectQuery:

• Pros:
  • Real-time data: Shows the latest information in the fact table as soon as it's available in the source.
  • Smaller model size: Reduces file size and improves deployment speed.
• Cons:
  • Slower performance: Queries can be slower, especially for complex calculations or large datasets.
  • Source dependency: Relies on continuous availability of the data source.
  • Limited filtering and slicing: Filter and slice operations can be slower or restricted compared to imported data.

General Best Practices:

• Use Import for smaller, frequently used dimensions: This ensures fast query performance and offline accessibility.
• Consider DirectQuery for frequently updated dimensions: Especially if real-time insights are crucial.
• Use DirectQuery for large, less frequently queried facts: This keeps the model size manageable and minimizes refresh times.
• Use Import for highly aggregated facts: Pre-aggregation in Power BI can significantly improve query performance on large datasets.
• Always evaluate the trade-offs: Consider the specific data size, query complexity, reporting needs, and data source limitations before choosing a mode.
  

Hope this helps. Please let us know if you have any further questions.

[HamidBee]

Thanks for sharing.

[Anonymous]

Hi @HamidBee 
We haven’t heard from you on the last response and was just checking back to see if your query got resolved. Otherwise, will respond back with the more details and we will try to help.
Thanks