Query Folding in Power BI | Complete Guide

Query Folding is a process where the steps of data transformation applied in the Power Query Editor are translated into native query language, that are then executed directly in the data source.
In this video I have covered below topics:
1. Why Query Folding is Important
2. Minimum Requirement for Folding
3. Checking Query Folding Native Query on each Transformation
4. Optimizing Reports using Query Folding
Data Used:
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[@sachinawati6332]

one of the best channel to learn power bi concepts

[@pivotalstats]

Thanks for the appreciation buddy!

[@hemanthboyapati3372]

I Finally understood query folding in detail. Thank you!

[@pivotalstats]

You are welcome!

[@kebincui]

Clearly explained. Thank you.

[@pivotalstats]

You are welcome!

[@HarishKumar-lz2nw]

Very well explained. Thanks

[@pivotalstats]

Glad you liked it

[@Tattysnuc]

Thank you. An excellent explanation.

[@pivotalstats]

Glad you enjoyed it!

[@GamerShaggy]

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[@pivotalstats]

Great suggestion! Noted. Thanks..👍

[@tidyverse-lg5yo]

Top! Thank youuu

[@pivotalstats]

You're welcome!

[@statesman6379]

I asked ChatGPT, “Is there a mode that does not support query folding?” Response: Yes, there is a mode in Power BI where query folding is not applicable: Import Mode. In Import Mode, data is loaded from the data source into the Power BI model, and all transformations are applied within the Power Query Editor before the data is loaded. Since the data is already loaded into the Power BI model, there is no need for query folding because there are no queries being sent back to the data source during report interactions. However, when discussing Dual Storage (composite models), it's important to note that the model can contain both imported data and DirectQuery-connected tables. For the imported data (i.e., tables loaded in Import Mode), query folding occurs during the data loading process within the Power Query Editor before the data is loaded into the model. For DirectQuery-connected tables, Power BI attempts to fold supported transformations back to the data source, leveraging the query engine of the data source.

[@pivotalstats]

👍